<p><strong>Data Architect</strong></p><p><em>Contract-to-permanent</em></p><p>The Data Architect is responsible for defining, governing, and evolving the organization’s enterprise data architecture across ERP, operational systems, and analytics platforms. This role ensures data consistency, scalability, and integrity as the organization executes ERP implementations and OpCo rollouts.</p><p>This position does <strong>not</strong> perform day-to-day reporting or operational data fixes. Instead, it defines the structure, standards, and guardrails that others operate within.</p><p><strong>Key Responsibilities</strong></p><p> </p><p>Data Architecture and Design</p><ul><li>Define and maintain enterprise data models across ERP, operational, and analytics platforms.</li><li>Design canonical data models for core domains such as customers, vendors, jobs, projects, financials, and assets.</li><li>Define data relationships and ownership across BuildOps, Procore, ERP finance, and downstream analytics systems.</li><li>Establish standards for master data, reference data, and transactional data.</li></ul><p>Data Governance and Quality</p><ul><li>Define data ownership, stewardship, and accountability by domain.</li><li>Establish data quality rules, validation standards, and reconciliation frameworks.</li><li>Partner with Applications Management and Operations Success Managers to align system configuration with data standards.</li><li>Define auditability and traceability standards for financial and operational data.</li></ul><p>Integration and Analytics Enablement</p><ul><li>Partner with integration engineers to define data contracts, schemas, and transformation rules.</li><li>Ensure data models support reporting, business intelligence, and downstream analytics use cases.</li><li>Review and approve data design decisions for new integrations and ERP modules.</li></ul><p>ERP and Implementation Support</p><ul><li>Support ERP implementations by validating data design, mappings, and cutover readiness.</li><li>Review data migration strategies to ensure alignment with target-state architecture.</li><li>Provide architectural guidance during fit-gap, design, and testing phases.</li></ul><p><br></p>
We are looking for a senior-level Data Engineer to shape and deliver a scalable data platform in Kalamazoo, Michigan. This role combines strategic architecture with hands-on engineering, creating reliable data products that support reporting, advanced analytics, and AI-driven solutions. The ideal candidate will build secure, multi-tenant data capabilities with strong attention to privacy, governance, and long-term platform quality.<br><br>Responsibilities:<br>• Lead the design of a modern data platform that supports ingestion, transformation, storage, and consumption across analytical and operational use cases.<br>• Build and maintain robust batch and streaming pipelines that move data from relational systems, object storage, document databases, and event sources into centralized platforms.<br>• Define data architecture standards, modeling approaches, and engineering practices that improve consistency, reliability, and scalability across the organization.<br>• Create multi-tenant data solutions with strong isolation controls, secure access patterns, and governance measures built into the platform design.<br>• Develop data models and serving layers that enable enterprise reporting, self-service analytics, and AI or machine learning workloads.<br>• Evaluate cloud-based data services, processing frameworks, and warehouse technologies to ensure the platform meets performance, cost, and security expectations.<br>• Partner with product, engineering, and leadership teams to explain technical decisions, highlight risks, and align platform investments with business priorities.<br>• Oversee external vendors and implementation partners by reviewing recommendations, challenging misaligned approaches, and enforcing internal data standards.
<p>We are seeking a Data Engineer to join the Enterprise Applications team with a Higher Education client. This role is responsible for designing, building, and maintaining systems for collecting, storing, integrating, and analyzing data from multiple sources across the organization.</p><p><br></p><p>The Data Engineer will support a major admissions technology initiative involving the implementation of Slate CRM and will serve as a key resource for data conversion, migration, integration development, and data architecture efforts. The role will also contribute to data governance, security, and AI readiness initiatives.</p><p><br></p><p>This is a 6 month contract to hire role.</p><p><br></p><p><u>Responsibilities</u></p><ul><li>Collaborate with stakeholders to understand reporting, data, and analytics requirements.</li><li>Design, implement, document, and maintain data lakes and related data architectures.</li><li>Support data conversion, migration, and integration activities associated with the Slate CRM implementation.</li><li>Develop and maintain integrations between enterprise systems and applications.</li><li>Create and maintain data models, including star schema and dimensional models.</li><li>Prepare data environments for artificial intelligence (AI) adoption and usage.</li><li>Recommend technical solutions that align with business requirements.</li><li>Provide technical support for enterprise data systems and users.</li><li>Develop and maintain technical documentation, user guides, and operational procedures.</li><li>Manage system upgrades and enhancements, including testing and documentation updates.</li><li>Troubleshoot data access, data quality, and integration issues.</li><li>Develop and implement security configurations and support compliance with governance standards.</li><li>Create data validation methods and processes to ensure data accuracy and reliability.</li><li>Monitor system and integration performance and identify improvement opportunities.</li><li>Collaborate with internal teams and external vendors regarding system enhancements, fixes, and integrations.</li><li>Participate in planning and implementation of data-related initiatives.</li></ul>
We are looking for a Data Engineer to join a real estate and property organization in Chicago, Illinois on a contract-to-permanent basis. This role is ideal for a hands-on builder who can create and improve modern data pipelines, manage core data platforms, and support reliable data delivery across the business. You will work within the Azure ecosystem to develop scalable solutions that connect multiple data sources, strengthen data quality, and enable informed decision-making.<br><br>Responsibilities:<br>• Design, build, and enhance end-to-end data pipelines using Microsoft Fabric and/or Azure Data Factory for production use.<br>• Manage and improve the data environment with a strong ownership mindset, ensuring performance, reliability, and maintainability.<br>• Integrate data from varied sources such as APIs, databases, and flat files into structured, usable datasets.<br>• Develop data models and schema designs that support reporting, analytics, and downstream business needs.<br>• Monitor data quality and implement validation checks, troubleshooting issues through root cause analysis and continuous optimization.<br>• Create scalable cloud-based data solutions within Azure that support long-term operational and analytical goals.<br>• Partner with cross-functional stakeholders to translate business questions into practical data engineering solutions.<br>• Contribute to orchestration, automation, and ongoing support of data workflows using modern engineering tools and programming languages.
We are looking for a Data Engineer to help shape and scale a modern cloud-based data environment in Wood Dale, Illinois. This contract opportunity with potential for a permanent role is ideal for someone who enjoys creating reliable data solutions from the ground up and turning disconnected information into trusted reporting assets. You will work closely with business and technical partners to build a strong data foundation that improves visibility, consistency, and decision-making. The role offers a hands-on chance to define standards, streamline data delivery, and support long-term scalability in a collaborative team setting.<br><br>Responsibilities:<br>• Create and refine scalable data models and curated datasets within BigQuery to support accurate analysis and reporting.<br>• Build, manage, and optimize ETL workflows and data pipelines that connect information from SaaS applications and other source systems.<br>• Develop reporting-ready data structures and dashboards that provide clear, dependable insights for business users.<br>• Establish data quality practices, documentation standards, and performance metrics to strengthen trust in enterprise reporting.<br>• Collaborate with cross-functional stakeholders to translate reporting objectives into well-structured data solutions.<br>• Automate repetitive data tasks through scripting and lightweight engineering approaches using tools such as Python.<br>• Apply governance and maintainability best practices to improve how data is organized, accessed, and supported over time.<br>• Contribute to modernization efforts by helping move data processes away from legacy workflows into scalable cloud-based platforms.
<p>We are looking for a Data Engineer to join an opportunity in Atlanta, Georgia. In this role, you will design and support reliable data solutions that enable efficient reporting, analytics, and downstream business insights across cloud-based platforms. The ideal candidate brings strong engineering fundamentals, enjoys working with diverse data sets, and can help shape scalable architecture in a collaborative enterprise environment.</p><p><br></p><p>Responsibilities:</p><p>• Design, build, and maintain robust data pipelines that move and transform information from a variety of internal and external sources.</p><p>• Develop efficient integration processes to unify structured and unstructured data for analytics, reporting, and operational use cases.</p><p>• Improve the speed, reliability, and scalability of existing data workflows through tuning, monitoring, and process optimization.</p><p>• Create and refine data models that support business intelligence, advanced analytics, and decision-making needs.</p><p>• Administer and enhance cloud-based data environments across modern platforms, ensuring stability, security, and performance.</p><p>• Partner closely with analytics and business teams to understand data needs and deliver accessible, high-quality datasets.</p><p>• Implement ETL solutions using Python, Spark, and cloud-native services to support enterprise data operations.</p><p>• Contribute to best practices for data engineering, documentation, and cross-functional collaboration within a consultative delivery model</p>
We are looking for a Data Engineer to join a growing team in Conshohocken, Pennsylvania within the financial services industry. In this role, you will build and enhance modern data pipelines and warehouse structures that support reporting, analytics, and business decision-making. You will partner with technical and business teams to deliver reliable, well-governed data solutions using Python, Azure Synapse Analytics, and related cloud technologies.<br><br>Responsibilities:<br>• Build and support scalable data pipelines using Python, including PySpark, within Azure Synapse Analytics notebooks and pipeline workflows.<br>• Design, load, and maintain warehouse structures in a massively parallel processing environment, applying dimensional modeling concepts such as facts and dimensions.<br>• Ingest and transform data from a range of sources, including APIs, databases, and flat files, to create dependable datasets for downstream use.<br>• Improve the efficiency and reliability of Azure Synapse processes by tuning queries, refining workloads, and addressing performance constraints.<br>• Partner with data architects, analysts, and other stakeholders to translate business needs into practical data models and engineering solutions.<br>• Establish validation routines and data quality controls to promote completeness, consistency, and accuracy across datasets.<br>• Monitor scheduled jobs and pipeline activity, troubleshoot failures, and implement corrective actions to maintain service levels.<br>• Document data flows, transformation logic, technical configurations, and operating procedures to support maintainability and knowledge sharing.<br>• Apply security, privacy, and governance standards to data solutions while supporting broader data platform initiatives such as lakes, lakehouses, and cataloging practices.
<ul><li>Design, build, and optimize scalable data pipelines for ingesting, processing, and transforming large datasets</li><li>Develop and maintain ETL/ELT workflows from multiple structured and unstructured data sources</li><li>Build data models and optimize data warehouse performance for analytics and reporting</li><li>Ensure data quality, integrity, governance, and security across all data platforms</li><li>Partner with business stakeholders, analysts, data scientists, and application teams to understand data requirements</li><li>Monitor pipeline performance and troubleshoot data-related issues in production environments</li><li>Implement automation for data validation, monitoring, and alerting</li><li>Support cloud-based data infrastructure and architecture improvements</li><li>Create and maintain documentation for data flows, architecture, and processes</li><li>Continuously improve data engineering standards, tools, and best practices</li></ul>
<ul><li>Design, build, and optimize scalable data pipelines for ingesting, processing, and transforming large datasets</li><li>Develop and maintain ETL/ELT workflows from multiple structured and unstructured data sources</li><li>Build data models and optimize data warehouse performance for analytics and reporting</li><li>Ensure data quality, integrity, governance, and security across all data platforms</li><li>Partner with business stakeholders, analysts, data scientists, and application teams to understand data requirements</li><li>Monitor pipeline performance and troubleshoot data-related issues in production environments</li><li>Implement automation for data validation, monitoring, and alerting</li><li>Support cloud-based data infrastructure and architecture improvements</li><li>Create and maintain documentation for data flows, architecture, and processes</li><li>Continuously improve data engineering standards, tools, and best practices</li></ul>
<p>Design and manage data pipelines, ensuring optimized performance for analytics and reporting. Support BI tools to provide actionable insights for decision-making.</p><p><br></p>
<p>We are seeking a <strong>Data Engineer</strong> with strong experience in <strong>Microsoft Azure</strong> and <strong>Databricks</strong> to help design, build, and maintain modern cloud-based data solutions. This individual will play a key role in developing scalable data pipelines, optimizing data architectures, and enabling business intelligence and analytics initiatives across the organization.</p><p>This is an excellent opportunity for someone passionate about cloud technologies, big data, and transforming raw data into actionable insights.</p><p>Responsibilities</p><ul><li>Design, develop, and maintain scalable data pipelines in Azure and Databricks</li><li>Build and optimize ETL/ELT processes for structured and unstructured data</li><li>Develop and support data lake, data warehouse, and analytics solutions</li><li>Integrate data from multiple internal and external sources</li><li>Collaborate with business analysts, data scientists, and stakeholders to understand data requirements</li><li>Ensure data quality, integrity, security, and governance standards are met</li><li>Monitor and troubleshoot data workflows and performance issues</li><li>Create and maintain technical documentation and data models</li><li>Support reporting and analytics initiatives by delivering reliable datasets</li></ul><p><br></p>
<p>We are looking for a fully remote Data Engineer to support and enhance a modern data environment serving critical business reporting and analytics needs. This role will focus on maintaining reliable warehouse operations while expanding scalable data pipelines and improving how information is integrated across systems. This position is well suited for someone who enjoys hands-on engineering work, thoughtful data design, and close collaboration with technical stakeholders.</p><p><br></p><p>Responsibilities:</p><p>• Oversee the daily performance, stability, and upkeep of the data warehouse to ensure dependable access to trusted data.</p><p>• Design, build, and refine data pipelines that move and transform information efficiently across multiple platforms.</p><p>• Develop engineering solutions using Python, Spark, and Databricks to support large-scale data processing and analytics workloads.</p><p>• Create and maintain SQL-based data structures and workflows that improve data quality, usability, and consistency.</p><p>• Apply sound data modeling practices to organize datasets for reporting, analysis, and downstream application use.</p><p>• Partner with cross-functional teams to understand integration needs and deliver scalable data solutions aligned with business priorities.</p><p>• Support cloud-based data movement and orchestration processes, including work involving Azure Data Factory where needed.</p><p>• Contribute to reporting and visualization readiness by preparing well-structured datasets for tools such as Power BI, Tableau, or Looker.</p>
We are looking for an experienced Data Engineer to help design and support scalable cloud-based data platforms in Jacksonville, Florida. This role focuses on building resilient data solutions in Azure, improving end-to-end data processing, and helping ensure strong performance across distributed systems. You will work closely with global engineering partners, contribute technical direction, and support a reliable delivery model in an Agile environment.<br><br>Responsibilities:<br>• Design, implement, and maintain cloud data infrastructure within Azure, using automation and infrastructure-as-code practices to improve consistency and scalability.<br>• Build and enhance enterprise data pipelines for ingestion, transformation, and processing using Databricks, Apache Spark, and Azure Data Factory.<br>• Provide technical leadership for cloud data platforms by driving architecture decisions that strengthen availability, performance, and long-term scalability.<br>• Collaborate daily with offshore and international engineering teams to align on development priorities, review code, and share technical knowledge across time zones.<br>• Participate actively in Agile ceremonies such as sprint planning, stand-ups, backlog refinement, readiness reviews, and retrospectives to support predictable delivery.<br>• Mentor data engineers through coaching, design guidance, and code review feedback that promotes high engineering standards.<br>• Support production operations by investigating incidents, resolving system bottlenecks, and leading root-cause analysis to improve platform reliability.<br>• Create and maintain architecture documentation, operational runbooks, and technical decision records to support distributed team execution.
<p>Robert Half is seeking a <strong>Contract Data Engineer</strong> to support our client’s data and analytics initiatives. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure that enable efficient data ingestion, transformation, and delivery. The ideal candidate has strong experience working with modern data platforms, cloud environments, and large-scale datasets.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><ul><li><strong>Data Pipeline Development:</strong> Design, build, and maintain scalable ETL / ELT pipelines to ingest, transform, and deliver data from multiple sources.</li><li><strong>Data Architecture:</strong> Develop and optimize data models, schemas, and warehouse structures to support analytics, reporting, and business intelligence needs.</li><li><strong>Cloud Data Platforms:</strong> Work within cloud environments such as <strong>AWS, Azure, or GCP</strong> to deploy and manage data solutions.</li><li><strong>Data Warehousing:</strong> Design and support enterprise data warehouses using platforms such as <strong>Snowflake, Redshift, BigQuery, or Azure Synapse</strong>.</li><li><strong>Big Data Processing:</strong> Develop solutions using big data technologies such as <strong>Spark, Databricks, Kafka, and Hadoop</strong> when required.</li><li><strong>Performance Optimization:</strong> Tune queries, pipelines, and storage solutions for performance, scalability, and cost efficiency.</li><li><strong>Data Quality & Reliability:</strong> Implement monitoring, validation, and alerting processes to ensure data accuracy, integrity, and availability.</li><li><strong>Collaboration:</strong> Work closely with Data Analysts, Data Scientists, Software Engineers, and business stakeholders to understand requirements and deliver data solutions.</li><li><strong>Documentation:</strong> Maintain detailed documentation for pipelines, data flows, and system architecture.</li></ul><p><br></p>
We are looking for a Data Engineer to help transform business data into reliable, accessible insights that support decision-making across the organization. This role partners with teams such as asset management, acquisitions, accounting, and HR to build reporting solutions, improve data quality, and streamline access to critical information. Based in Los Angeles, California, the position is well suited for someone who enjoys combining technical expertise with business collaboration in a fast-moving environment.<br><br>Responsibilities:<br>• Build and enhance dashboards, reports, and automated data workflows using tools such as Python, Excel, and Power BI.<br>• Translate business questions into scalable reporting and analytics solutions by working closely with stakeholders across multiple departments.<br>• Examine large and complex datasets to uncover trends, exceptions, and actionable insights that support operational and strategic decisions.<br>• Design and maintain data extraction, transformation, and loading processes, including query development and performance optimization.<br>• Monitor data accuracy through regular validation, issue resolution, and ongoing improvements to data governance practices.<br>• Support and guide entry-level BI team members by reviewing work, sharing best practices, and encouraging career growth.<br>• Explain technical findings in a clear way to non-technical audiences to promote understanding and adoption of data solutions.<br>• Lead or contribute to cross-functional initiatives that improve data accessibility, usability, and reporting effectiveness across the business.<br>• Administer BI platforms to maintain performance, reliability, and appropriate security controls.<br>• Deliver user support and training to help employees make effective use of reporting tools and interpret data confidently.
<p><strong>Key Responsibilities</strong></p><p><strong>Leadership & Team Mentoring </strong></p><ul><li>Lead, mentor, and develop a team of data engineers and BI developers.</li><li>Communicate business priorities, define goals, and establish clear KPIs to track performance and delivery.</li><li>Foster a collaborative and learning-oriented culture across technical and business functions.</li></ul><p><strong>Data Engineering </strong></p><ul><li>Design, build, and maintain scalable and efficient data pipelines and integrations across multiple internal and external systems.</li><li>Oversee ETL/ELT processes ensuring data accuracy, reliability, and timeliness.</li><li>Manage data models and data warehouse structures optimized for reporting, analytics, and advanced use cases (e.g., predictive modeling, machine learning).</li><li>Implement best practices in data architecture, automation, and version control (e.g., Git).</li></ul><p><strong> </strong></p><p><strong> </strong></p><p><strong>Business Intelligence & Reporting</strong></p><ul><li>Oversee the design and delivery of SSRS and Power BI dashboards, ensuring usability and alignment with business goals.</li><li>Establish and manage data visualization standards, reusable datasets, and semantic models for self-service analytics.</li><li>Collaborate with business stakeholders to gather requirements and translate them into technical specifications and BI solutions.</li></ul><p><br></p>
We are looking for a Data Scientist to join a fast-paced investment environment in New York, New York, where data-driven insight plays a central role in research and decision-making. This position will focus on turning complex datasets into practical analysis, scalable tools, and clear intelligence that support investment ideas. The ideal candidate brings strong technical depth, sound statistical judgment, and the ability to shape loosely defined questions into structured, repeatable research.<br><br>Responsibilities:<br>• Work closely with investment professionals to create quantitative studies, analytical frameworks, and practical tools that strengthen fundamental research workflows.<br>• Identify promising alternative data sources, assess their relevance and quality, and support their integration into the research process.<br>• Design and execute backtests, predictive models, and exploratory investigations to evaluate and refine investment hypotheses.<br>• Produce and maintain analyst-facing dashboards and reporting views within internal analytics environments.<br>• Convert one-off research requests into repeatable, clearly documented analyses that can be reused and scaled over time.<br>• Partner with engineering teams to define data needs, support ingestion processes, and improve dataset availability for research use.
We are looking for a Data Scientist to support AI and machine learning initiatives that advance patient care, research, and operational decision-making in Palo Alto, California. This is a Contract position focused on turning healthcare data into practical, high-impact solutions through model development, validation, and deployment. The role works closely with clinical, research, and operational partners to translate complex problems into scalable analytical approaches while maintaining strong standards for quality, fairness, and performance.<br><br>Responsibilities:<br>• Create, implement, and support AI- and ML-driven workflows that improve clinical, research, and administrative processes.<br>• Partner with cross-functional stakeholders to define analytical needs and deliver data science solutions aligned with healthcare use cases.<br>• Assess and refine tools, platforms, and methods used to manage model development, deployment, and ongoing lifecycle activities.<br>• Train, test, and validate internally developed or externally sourced machine learning models using hospital data and established quality controls.<br>• Perform bias reviews and model performance checks to help ensure responsible and reliable use of predictive algorithms.<br>• Analyze large-scale healthcare datasets using Python, R, SQL, and cloud-based or distributed computing environments.<br>• Work alongside clinicians and researchers to adapt analytical methods for real-world use in care delivery and related settings.
<p><strong>Healthcare Data Analyst </strong></p><p>We’re seeking a Data Analyst to join a healthcare company and help drive improved patient outcomes through data-driven insights. In this role, you will analyze clinical and operational data to identify trends, support quality improvement initiatives, and enhance overall care delivery.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><ul><li>Develop and maintain reports and interactive dashboards </li><li>Analyze patient, quality, and operational data to identify opportunities for improvements</li></ul><p><strong>Qualifications:</strong></p><ul><li>Experience working with healthcare data in a hospital or clinical environment</li><li>Strong skills in reporting and dashboard tools (e.g., Power BI, Tableau, or similar)</li><li>Proficiency in SQL and/or Excel for data analysis</li><li>Ability to communicate findings clearly to both technical and non-technical audiences</li></ul><p><br></p>
<p>Robert Half is looking for a Data Analyst to support a well-respected and thriving company! The Data Analyst will be supporting the Marketing Department on a multi-faceted, stimulating project. Are you a new graduate looking to start your career, or an accomplished Data Analyst looking to expand your talents? Apply today! Working Monday-Friday, 8am-5pm in Enon, Ohio the Data Analyst will be ensuring accurate item pricing all the way to store level. This is a long-term contract opportunity with a fantastic growing company and could go contract to permanent based on performance.</p><p> </p><p>Responsibilities</p><p>- Coordinating information between company and vendors to ensure proper pricing for merchandise</p><p>- Researching and analyzing new products, product pricing, pricing exceptions, and ensuring appropriate classifications</p><p>- Identifying pricing implementation issues, recommending solutions, and communicating the course of action within the organization</p><p>- Heavy data entry of pricing information</p><p>- Interacting with vendors to obtain appropriate information</p><p> </p><p><strong>If you are interested, call 937.224.8326 today!</strong></p>
We are looking for a Data Analyst to join a project-focused team supporting reinsurance operations in South Portland, Maine. This contract opportunity with permanent potential is ideal for someone who can evaluate reporting needs, uncover root causes behind data issues, and recommend more effective ways to deliver meaningful insights. The role blends analytical thinking with hands-on technical execution, with a strong emphasis on improving reporting, supporting financial accuracy, and building dependable data solutions.<br><br>Responsibilities:<br>• Analyze reporting requests to identify the true business need, investigate underlying data challenges, and design practical reporting solutions.<br>• Redesign and enhance existing reports to improve usability, accuracy, and decision-making value for stakeholders.<br>• Build and maintain recurring and ad hoc reports using tools such as Power BI, Excel, SQL, and DAX.<br>• Develop and validate data feeds that support accrual processing and ensure accurate flow of information into the subledger.<br>• Perform reconciliations and review output for completeness, consistency, and alignment with financial reporting requirements.<br>• Support automation efforts related to accrual and reporting workflows to reduce manual effort and increase reliability.<br>• Partner with accounting, data management, and business teams to translate operational needs into scalable data deliverables.<br>• Apply reinsurance knowledge to interpret data correctly and ensure reporting reflects relevant business activity.
<p>We are looking for a Data Administrator to join our team in a contract role with the potential to become permanent. This opportunity is well suited for an early-career candidate with at least one year of post-graduate experience who enjoys working with data, spotting irregular patterns, and supporting fraud-related analysis. The position follows a 2 day a week hybrid schedule with in-office collaboration</p><p><br></p><p>Responsibilities:</p><p>• Review operational and analytical data sets to identify anomalies, trends, and indicators related to suspected fraudulent activity.</p><p>• Monitor routine data processes with accuracy and consistency, ensuring issues are flagged quickly and escalated when needed.</p><p>• Support fraud analysis efforts by examining patterns, validating findings, and helping improve visibility into risk areas.</p><p>• Investigate data discrepancies and partner with internal stakeholders to resolve errors affecting reporting or operations.</p><p>• Maintain data quality across reports, tracking tools, and internal systems used for analysis and decision-making.</p><p>• Prepare clear summaries of findings and communicate insights that help teams respond to anti-fraud concerns effectively.</p><p>• Assist with updates to workflows, reporting methods, or system-related processes as business needs evolve.</p><p>• Contribute to a growing team environment by taking on new responsibilities over time and supporting continuous improvement initiatives.</p>
We are looking for a detail-oriented Data Analyst to join a Financial Services team in New Orleans, Louisiana on a contract basis with the potential for a permanent position. This role focuses on reviewing data tied to potential fraud activity, identifying irregularities in invoices and transactions, and turning findings into clear recommendations for business partners. The ideal candidate is comfortable working with large data sets, performing research, and using analytical tools to support fraud detection and investigation efforts.<br><br>Responsibilities:<br>• Analyze transaction and invoice data to detect unusual patterns, inconsistencies, and indicators of potentially fraudulent activity.<br>• Investigate flagged records by conducting research, validating supporting details, and documenting findings in a clear and organized manner.<br>• Use Microsoft Excel and related analytical methods to sort, reconcile, and interpret large volumes of financial information.<br>• Partner with internal stakeholders to communicate trends, summarize risks, and support decisions related to fraud prevention and resolution.<br>• Review invoice discrepancies and related exceptions to determine root causes and recommend next steps.<br>• Maintain accurate reporting on case activity, analytical results, and emerging fraud patterns for ongoing monitoring.<br>• Support anti-fraud initiatives by refining data review processes and improving the quality of investigative insights.
<p>Robert Half is seeking a Contract Data Analyst to join our client's team. As a Data Analyst, you will be responsible for collecting, processing, and analyzing data to provide actionable insights that support business decisions. This contract position offers an exciting opportunity to work with a dynamic team and help drive data-driven strategies for a respected organization.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><ol><li><strong>Data Collection and Analysis:</strong> Collect, clean, and analyze data from various sources to identify trends, patterns, and insights that inform business decisions.</li><li><strong>Reporting:</strong> Create and maintain dashboards, reports, and visualizations that communicate findings to stakeholders in a clear and concise manner.</li><li><strong>Data Validation:</strong> Ensure data integrity by conducting regular audits, validation, and quality checks.</li><li><strong>Collaboration:</strong> Work closely with cross-functional teams to understand data requirements and provide insights that support strategic goals.</li><li><strong>Data Modeling:</strong> Develop and maintain data models, forecasts, and simulations to support business planning and operations.</li><li><strong>Trend Analysis:</strong> Monitor key performance indicators (KPIs) and analyze data trends to identify opportunities for improvement.</li><li><strong>Documentation:</strong> Document data processes, methodologies, and findings to ensure transparency and reproducibility of results.</li><li><strong>Ad Hoc Analysis:</strong> Provide ad hoc analysis and reporting support as needed to assist in decision-making processes.</li></ol><p><br></p>
We are looking for a Data Analyst to join a long-term contract opportunity in Oklahoma City, Oklahoma. In this role, you will evaluate business workflows, examine complex datasets, and uncover issues that affect data accuracy and operational performance. The position calls for someone who can translate findings into practical recommendations, build reporting solutions, and collaborate effectively with stakeholders across technical and business teams.<br><br>Responsibilities:<br>• Analyze large and complex datasets to identify inconsistencies, root causes, and opportunities to strengthen data reliability and business performance<br>• Create, test, and refine SQL queries, functions, and stored procedures to support scheduled reporting as well as one-time business requests<br>• Develop reporting and data collection solutions that improve efficiency, enhance visibility into operations, and support informed decision-making<br>• Examine trends, anomalies, and performance patterns in data and present meaningful insights to business leaders and project stakeholders<br>• Review reports, source data, and existing logic to detect defects, resolve data quality concerns, and improve overall output accuracy<br>• Document current business processes, workflows, and analytical findings while recommending practical improvements based on observed issues<br>• Perform data quality reviews and validation activities to ensure information is complete, accurate, and fit for reporting purposes<br>• Build a strong understanding of organizational procedures and operational workflows in order to align analysis with business needs<br>• Apply critical thinking and structured problem-solving to support fraud-related analysis, process improvement efforts, and cross-functional initiatives