We are looking for a skilled Data Engineer to join our logistics team in Lithonia, Georgia. In this role, you will design, construct, and maintain data pipelines and infrastructure to support analytics and operational systems. You will play a key role in enabling data visualization tools, optimizing data processes, and ensuring the accuracy and availability of critical information.<br><br>Responsibilities:<br>• Design and implement data pipelines to efficiently extract, transform, and load data from multiple sources.<br>• Develop and maintain data models and storage solutions to support analytics and reporting needs.<br>• Collaborate with stakeholders to troubleshoot data inconsistencies and resolve technical issues.<br>• Utilize Tableau or Power BI to create meaningful data visualizations that drive business insights.<br>• Write and optimize database procedures, triggers, and other SQL-based functionalities.<br>• Manage and monitor databases to ensure their performance and reliability.<br>• Provide technical guidance to analysts on best practices in data governance and performance optimization.<br>• Participate in cross-functional projects to enhance data accessibility and quality across departments.<br>• Explore and integrate Python-based solutions to enhance data engineering processes.<br>• Assist in training and development related to data availability and analytics tools.
We are looking for an experienced Senior Data Engineer to join our team in Atlanta, Georgia. This role is ideal for someone with a strong background in data architecture, cloud platforms, and analytics tools. You will play a key role in designing, building, and optimizing data systems to support business operations and decision-making.<br><br>Responsibilities:<br>• Develop and maintain scalable data models and database designs to support business needs.<br>• Implement and manage data integration workflows using ETL processes and tools.<br>• Build and optimize data lakes and LakeHouse architectures on Azure platforms.<br>• Utilize Microsoft Fabric and Azure Databricks to create advanced data solutions.<br>• Design and develop dashboards and reports using Power BI to provide actionable insights.<br>• Ensure data governance by establishing policies, procedures, and standards for data use.<br>• Collaborate with cross-functional teams to align data strategies with organizational goals.<br>• Leverage Python and SQL for data analysis, transformation, and automation.<br>• Work with middleware solutions like MuleSoft for efficient data communication and integration.<br>• Stay updated on emerging technologies to continuously improve data engineering practices.
We are looking for a skilled Data Engineer to support our organization's data initiatives in Savannah, Georgia. This Contract to permanent role focuses on managing, optimizing, and securing data systems to drive strategic decision-making and improve overall performance. The ideal candidate will work closely with technology teams, analytics departments, and business stakeholders to ensure seamless data integration, accuracy, and scalability.<br><br>Responsibilities:<br>• Design and implement robust data lake and warehouse architectures to support organizational needs.<br>• Develop efficient ETL pipelines to process and integrate data from multiple sources.<br>• Collaborate with analytics teams to create and refine data models for reporting and visualization.<br>• Monitor and maintain data systems to ensure quality, security, and availability.<br>• Troubleshoot data-related issues and perform in-depth analyses to identify solutions.<br>• Define and manage organizational data assets, including SaaS tools and platforms.<br>• Partner with IT and security teams to meet compliance and governance standards.<br>• Document workflows, pipelines, and architecture for knowledge sharing and long-term use.<br>• Translate business requirements into technical solutions that meet reporting and analytics needs.<br>• Provide guidance and mentorship to team members on data usage and best practices.
<p>We are looking for an experienced Data Engineer to join our team. This role involves working on a high-priority cloud migration project within a dynamic business unit. If you have a strong background in data engineering and are ready to contribute to an impactful initiative, we encourage you to apply.</p><p><br></p><p>Responsibilities:</p><p>• Develop and optimize data pipelines to support seamless migration to a cloud-based platform.</p><p>• Collaborate closely with the data analytics leader to align project objectives and deliverables.</p><p>• Utilize Python and Google Cloud Platform to create efficient and scalable data solutions.</p><p>• Integrate data from various SaaS applications into the cloud environment.</p><p>• Address challenges and uncertainties by designing innovative solutions during the early stages of data modernization.</p><p>• Ensure the accuracy and reliability of data ingestion processes across multiple groups.</p><p>• Monitor and maintain the performance of data pipelines to meet business needs.</p><p>• Provide regular updates on project progress and identify areas for improvement.</p><p>• Work independently while adhering to project timelines and requirements.</p>
We are looking for an experienced Lead Data Engineer to oversee the design, implementation, and management of advanced data infrastructure in Houston, Texas. This role requires expertise in architecting scalable solutions, optimizing data pipelines, and ensuring data quality to support analytics, machine learning, and real-time processing. The ideal candidate will have a deep understanding of Lakehouse architecture and Medallion design principles to deliver robust and governed data solutions.<br><br>Responsibilities:<br>• Develop and implement scalable data pipelines to ingest, process, and store large datasets using tools such as Apache Spark, Hadoop, and Kafka.<br>• Utilize cloud platforms like AWS or Azure to manage data storage and processing, leveraging services such as S3, Lambda, and Azure Data Lake.<br>• Design and operationalize data architecture following Medallion patterns to ensure data usability and quality across Bronze, Silver, and Gold layers.<br>• Build and optimize data models and storage solutions, including Databricks Lakehouses, to support analytical and operational needs.<br>• Automate data workflows using tools like Apache Airflow and Fivetran to streamline integration and improve efficiency.<br>• Lead initiatives to establish best practices in data management, facilitating knowledge sharing and collaboration across technical and business teams.<br>• Collaborate with data scientists to provide infrastructure and tools for complex analytical models, using programming languages like Python or R.<br>• Implement and enforce data governance policies, including encryption, masking, and access controls, within cloud environments.<br>• Monitor and troubleshoot data pipelines for performance issues, applying tuning techniques to enhance throughput and reliability.<br>• Stay updated with emerging technologies in data engineering and advocate for improvements to the organization's data systems.
We are looking for an experienced Data Engineer to join our team in Jacksonville, Florida. In this role, you will take the lead in designing and building a cutting-edge Azure lakehouse platform that enables business leaders to access analytics through natural language queries. This position combines hands-on technical expertise with leadership responsibilities, offering an opportunity to mentor a team of skilled engineers while driving innovation.<br><br>Responsibilities:<br>• Architect and develop a robust Azure lakehouse platform, utilizing Azure Data Lake Gen2, Delta Lake, and PySpark to create efficient data pipelines.<br>• Implement a semantic layer and metric store to ensure consistent data translation and definitions across the organization.<br>• Design and maintain real-time and batch data pipelines, incorporating medallion architecture, schema evolution, and data contracts.<br>• Build retrieval systems for large language models (LLMs) using Azure OpenAI and vectorized Delta tables to support chat-based analytics.<br>• Ensure data quality, lineage, and observability through tools like Great Expectations and Unity Catalog, while optimizing costs through partitioning and compaction.<br>• Develop automated systems for anomaly detection and alerting using Azure ML pipelines and Event Grid.<br>• Collaborate with product and operations teams to translate complex business questions into actionable data models and queries.<br>• Lead and mentor a team of data and Python engineers, establishing best practices in CI/CD, code reviews, and documentation.<br>• Ensure compliance with security, privacy, and governance standards by designing and implementing robust data handling protocols.
<p>We are looking for an experienced Senior Data Engineer to join our team in Denver, Colorado. In this role, you will design and implement data solutions that drive business insights and operational efficiency. You will collaborate with cross-functional teams to manage data pipelines, optimize workflows, and ensure the integrity and security of data systems.</p><p><br></p><p>Responsibilities:</p><p>• Develop and maintain robust data pipelines to process and transform large datasets effectively.</p><p>• Advise on tools / technologies to implement. </p><p>• Collaborate with stakeholders to understand data requirements and translate them into technical solutions.</p><p>• Design and implement ETL processes to facilitate seamless data integration.</p><p>• Optimize data workflows and ensure system performance meets organizational needs.</p><p>• Work with Apache Spark, Hadoop, and Kafka to build scalable data systems.</p><p>• Create and maintain SQL queries for data extraction and analysis.</p><p>• Ensure data security and integrity by adhering to best practices.</p><p>• Troubleshoot and resolve issues in data systems to minimize downtime.</p><p>• Provide technical guidance and mentorship to less experienced team members.</p><p>• Stay updated on emerging technologies to enhance data engineering practices.</p>
<p>We are looking for an experienced Senior Data Engineer to join our team. This role involves designing and implementing scalable data solutions, optimizing data workflows, and driving innovation in data architecture. The ideal candidate will possess strong leadership qualities and a passion for problem-solving in a fast-paced, cutting-edge environment.</p><p><br></p><p>Responsibilities:</p><p>• Develop high-performance data systems, including databases, APIs, and data integration pipelines, to support scalable solutions.</p><p>• Design and implement metadata-driven architectures and automate deployment processes using infrastructure-as-code principles.</p><p>• Promote best practices in software engineering, such as code reviews, testing, and continuous integration/delivery (CI/CD).</p><p>• Establish and maintain a robust data governance framework to ensure compliance and data integrity.</p><p>• Monitor processes and implement improvements, including query optimization, code refactoring, and efficiency enhancements.</p><p>• Leverage cloud platforms, particularly Azure and Databricks, to improve system architecture and scalability.</p><p>• Conduct data quality checks and build procedures to address and resolve data issues effectively.</p><p>• Create and maintain documentation for data architecture, standards, and best practices.</p><p>• Provide technical leadership to the team, guiding design discussions and fostering innovation in data infrastructure.</p><p>• Identify and implement opportunities for process optimization and automation to improve operational efficiency.</p>
<p>We are seeking a highly skilled Data Engineer to design, build, and manage our data infrastructure. The ideal candidate is an expert in writing complex SQL queries, designing efficient database schemas, and developing ETL/ELT pipelines. This role ensures data accuracy, accessibility, and performance optimization to support business intelligence, analytics, and reporting initiatives.</p><p><br></p><p><strong><em><u>Key Responsibilities</u></em></strong></p><p><br></p><p><strong>Database Design & Management</strong></p><ul><li>Design, develop, and maintain relational databases, including SQL Server, PostgreSQL, and Oracle, as well as cloud-based data warehouses.</li></ul><p><strong>Strategic SQL & Data Engineering</strong></p><ul><li>Develop advanced, optimized SQL queries, stored procedures, and functions to process and analyze large, complex datasets and deliver actionable business insights.</li></ul><p><strong>Data Pipeline Automation & Orchestration</strong></p><ul><li>Build, automate, and orchestrate ETL/ELT workflows using SQL, Python, and cloud-native tools to integrate and transform data from diverse, distributed sources.</li></ul><p><strong>Performance Optimization</strong></p><ul><li>Tune SQL queries and optimize database schemas through indexing, partitioning, and normalization to improve data retrieval and processing performance.</li></ul><p><strong>Data Integrity & Security</strong></p><ul><li>Ensure data quality, consistency, and integrity across systems.</li><li>Implement data masking, encryption, and role-based access control (RBAC).</li></ul><p><strong>Documentation</strong></p><ul><li>Maintain comprehensive technical documentation, including database schemas, data dictionaries, and ETL workflows.</li></ul>
<p>Position Overview</p><p>We are seeking a Data Engineer Engineer to support and enhance a Databricks‑based data platform during its development phase. This role is focused on building reliable, scalable data solutions early in the lifecycle—not production firefighting.</p><p>The ideal candidate brings hands‑on experience with Databricks, PySpark, Python, and a working understanding of Azure cloud services. You will partner closely with Data Engineering teams to ensure pipelines, notebooks, and workflows are designed for long‑term scalability and production readiness.</p><p><br></p><p>Key Responsibilities</p><ul><li>Develop and enhance Databricks notebooks, jobs, and workflows</li><li>Write and optimize PySpark and Python code for distributed data processing</li><li>Assist in designing scalable and reliable data pipelines</li><li>Apply Spark performance best practices: partitioning, caching, joins, file sizing</li><li>Work with Delta Lake tables, schemas, and data models</li><li>Perform data validation and quality checks during development cycles</li><li>Support cluster configuration, sizing, and tuning for development workloads</li><li>Identify performance bottlenecks early and recommend improvements</li><li>Partner with Data Engineers to prepare solutions for future production rollout</li><li>Document development standards, patterns, and best practices</li></ul>
<p>We’re looking for a <strong>Senior Data Engineer</strong> to design, build, and optimize modern data pipelines and architecture. You’ll support analytics, reporting, and data‑driven applications by creating scalable, efficient data systems across cloud environments.</p><p><strong>What You’ll Do</strong></p><ul><li>Design and build <strong>ETL/ELT pipelines</strong> across cloud platforms (Azure, AWS, or GCP)</li><li>Architect and maintain Data Lake / Lakehouse environments</li><li>Develop and optimize data ingestion, transformation, and orchestration workflows</li><li>Ensure data quality, reliability, and scalability across all pipelines</li><li>Collaborate with BI developers, analysts, and business stakeholders</li><li>Implement best practices around versioning, testing, and deployment</li><li>Support real‑time and batch data processing initiatives</li></ul><p><br></p>
<p>**** For Faster response on the position, please send a message to Jimmy Escobar on LinkedIn or send an email to Jimmy.Escobar@roberthalf(.com) with your resume. You can also call my office number at 424-270-9193****</p><p><br></p><p>We are looking for a skilled Data Engineer to join our team on a long-term contract basis in Los Angeles, California. In this role, you will design, build, and maintain robust data infrastructure to support business operations and analytics. This position offers an opportunity to work with cutting-edge technologies and contribute to impactful projects. This position is a hybrid that is 3 days a week on-site and 2 days remote.</p><p><br></p><p>Responsibilities:</p><p>• Develop and implement scalable data pipelines using Apache Spark, Hadoop, and other big data technologies.</p><p>• Collaborate with cross-functional teams to understand and translate business requirements into technical solutions.</p><p>• Create and maintain ETL processes to ensure data integrity and accessibility.</p><p>• Manage and monitor large-scale data processing systems, ensuring seamless operation.</p><p>• Design and deploy solutions for real-time data streaming using Apache Kafka.</p><p>• Perform advanced data analytics to support business decision-making.</p><p>• Troubleshoot and resolve issues related to data infrastructure and applications.</p><p><br></p>
<p>The Data Engineer role focuses on designing, building, and optimizing scalable data solutions that support diverse business needs. This position requires the ability to work independently while collaborating effectively in a fast-paced, agile environment. The individual in this role partners with cross-functional teams to gather data requirements, recommend enhancements to existing data pipelines and architectures, and ensure the reliability, performance, and efficiency of data processes.</p><p>Responsibilities</p><ul><li>Support the team’s adoption and continued evolution of the Databricks platform, leveraging features such as Delta Live Tables, workflows, and related tooling</li><li>Design, develop, and maintain data pipelines that extract data from relational sources, load it into a data lake, transform it as needed, and publish it to a Databricks-based lakehouse environment</li><li>Optimize data pipelines and processing workflows to improve performance, scalability, and overall efficiency</li><li>Implement data quality checks and validation logic to ensure data accuracy, consistency, and completeness</li><li>Create and maintain documentation including data mappings, data definitions, architectural diagrams, and data flow diagrams</li><li>Develop proof-of-concepts to evaluate and validate new technologies, tools, or data processes</li><li>Deploy, manage, and support code across non-production and production environments</li><li>Investigate, troubleshoot, and resolve data-related issues, including identifying root causes and implementing fixes</li><li>Identify performance bottlenecks and recommend optimization strategies, including database tuning and query performance improvements</li></ul>
<p>Since it’s 2026, the Data Engineering landscape in DC has shifted heavily toward <strong>Cloud-Native architectures</strong> and <strong>GenAI-ready pipelines</strong>. Robert Half typically recruits for both their internal corporate teams and their high-end consulting arm (Protiviti).</p><p>Here is a tailored job description based on current 2026 market standards and Robert Half’s specific hiring trends in the District.</p><p><br></p><p>Job Title: Data Engineer</p><p><strong>Location:</strong> Washington, DC (Hybrid – Downtown DC Office)</p><p><strong>Company:</strong> Robert Half </p><p><strong>Employment Type: </strong>Contract-to-Hire</p><p>Role Overview</p><p>As a Data Engineer at Robert Half, you will be the backbone of our data-driven decision-making process. You aren't just "moving data"; you are architecting the flow of information that powers our localized market analytics and global recruitment engines. In the DC market, this often involves handling high-compliance data environments and integrating cutting-edge AI frameworks into traditional ETL workflows.</p><p><br></p><p><br></p>
<p><strong>Data Pipeline Development</strong></p><ul><li>Design, build, and optimize scalable ETL/ELT pipelines to support analytics and operational workflows.</li><li>Ingest structured, semi-structured, and unstructured data from multiple internal and external sources.</li><li>Automate and orchestrate data workflows using tools like Airflow, Azure Data Factory, AWS Glue, or similar.</li></ul><p><strong>Data Architecture & Modeling</strong></p><ul><li>Develop and maintain data models, data marts, and data warehouses (relational, dimensional, and/or cloud-native).</li><li>Implement best practices for data partitioning, performance optimization, and storage management.</li><li>Work with BI developers, data scientists, and analysts to ensure datasets are structured to meet business needs.</li></ul><p><strong>Cloud Engineering & Storage</strong></p><ul><li>Build and maintain cloud data environments (Azure, AWS, GCP), including storage, compute, and security components.</li><li>Deploy and manage scalable data systems such as Snowflake, Databricks, BigQuery, Redshift, or Synapse.</li><li>Optimize cloud data cost, performance, and governance.</li></ul><p><strong>Data Quality & Reliability</strong></p><ul><li>Implement data validation, error handling, and monitoring to ensure accuracy, completeness, and reliability.</li><li>Troubleshoot pipeline failures, performance issues, and data discrepancies.</li><li>Maintain documentation and data lineage for transparency and auditability.</li></ul><p><strong>Collaboration & Cross‑Functional Support</strong></p><ul><li>Partner with product, engineering, and analytics teams to translate business requirements into technical solutions.</li><li>Support self-service analytics initiatives by preparing high-quality datasets and data products.</li><li>Provide technical guidance on data best practices and engineering standards.</li></ul><p><br></p><p><br></p>
<p>Essential Duties and Responsibilities:</p><p> · Knowledge of database coding and tables; as well as general database management</p><p> · Understanding of client management, support, and communicating progress and timelines accordingly</p><p> · Organizes and/or leads Informatics projects in the implementation/use of new data warehouse tools and systems</p><p> · Ability to train new hires; as well as lead in training of new client staff members</p><p> · Understanding data schema and the analysis of database performance and accuracy</p><p> · Understanding of ETL tools, OLAP design, and data quality processes</p><p> · Knowledge of Business Intelligence life cycle: planning, design, development, validation, deployment, documentation, and ongoing support</p><p> · Working knowledge of electronic medical records software (eCW, Nextgen, etc) and the backend storage of that data</p><p> · Ability to generate effective probability modeling and statistics as it pertains to healthcare outcomes and financial risks</p><p> · Ability to manage sometimes lengthy and complicated projects from throughout the life cycle and meet the deadlines associated with these projects</p><p> · Development, maintenance, technical support of various reports and dashboards</p><p> · Knowledge of Microsoft® SQL including coding language, creation of tables, stored procedures, and query design</p><p> · Fundamental understanding of outpatient healthcare workflows</p><p> · Knowledge of relational database concepts and flat/formatted file processing.</p><p> · Possesses strong commitment to data validation processes in order to ensure accuracy of reporting (internal quality control)</p><p> · Possesses a firm grasp of patient confidentiality and system security practices to prevent HIPAA and other security violations.</p><p> · Knowledge of IBM Cognos® or other database reporting software such as SAS, SPSS, and Crystal Reports</p><p> · Ability to meet the needs of other members of the Informatics department to maximize efficiency and minimize complexity of end-user products</p><p><br></p><p>Requirements:</p><p> · Education: Bachelor's Degree</p><p> · Proven experience as a dbt Developer or in a similar Data Engineer role.</p><p> · Expert-level SQL skills — capable of writing, tuning, and debugging complex queries across large datasets.</p><p> · Strong experience with Snowflake or comparable data warehouse technologies (BigQuery, Redshift, etc.).</p><p> · Proficiency in Python for scripting, automation, or data manipulation.</p><p> · Solid understanding of data warehousing concepts, modeling, and ELT workflows.</p><p> · Familiarity with Git or other version control systems.</p><p> · Experience working with cloud-based platforms such as AWS, GCP, or Azure.</p><p><br></p><p><br></p>
<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>We are looking for a skilled Data Engineer to design and enhance scalable data solutions that meet diverse business objectives. This role involves collaborating with cross-functional teams to identify data requirements, improve existing pipelines, and ensure efficient data processing. The ideal candidate will bring expertise in server-side development, database management, and software deployment, working in a dynamic and fast-paced environment.</p><p><br></p><p>Responsibilities</p><ul><li>Enhance and optimize existing data storage platforms, including relational and NoSQL databases, to improve data accessibility, performance, and persistence</li><li>Apply advanced database techniques such as tuning, indexing, views, and stored procedures to support efficient and reliable data management</li><li>Develop server-side Python services utilizing concurrency patterns such as asynchronous programming and multi-threading, and leveraging libraries such as NumPy and Pandas</li><li>Design, build, and maintain APIs using modern frameworks, with experience across communication protocols including gRPC and socket-based implementations</li><li>Create, manage, and maintain CI/CD pipelines using DevOps and artifact management tools to enable efficient and reliable software delivery</li><li>Design and deploy applications in enterprise Linux environments, ensuring stability, performance, and scalability</li><li>Partner with cross-functional teams to gather requirements and deliver technical solutions aligned with business objectives</li><li>Follow software development lifecycle best practices to ensure high-quality, maintainable, and secure solutions</li><li>Work effectively in iterative, fast-paced development environments while consistently delivering high-quality outcomes on schedule</li></ul><p><br></p>
<p>As a Data Engineer at Robert Half, you will be the backbone of our data-driven decision-making process. You aren't just "moving data"; you are architecting the flow of information that powers our localized market analytics and global recruitment engines. In the DC market, this often involves handling high-compliance data environments and integrating cutting-edge AI frameworks into traditional ETL workflows.</p>
We are looking for a skilled Data Engineer to join our team on a long-term contract basis. This role is based in West Des Moines, Iowa, and offers the opportunity to work on advanced data solutions that support organizational decision-making and efficiency. The ideal candidate will have expertise in relational databases, data cleansing, and modern data warehousing technologies.<br><br>Responsibilities:<br>• Develop, maintain, and optimize data pipelines to support business operations and analytics.<br>• Perform data extraction, transformation, and cleansing to ensure accuracy and reliability.<br>• Collaborate with teams to design and implement data warehouses and data lakes.<br>• Utilize Microsoft SQL Server to build and manage relational database structures.<br>• Analyze data sources and provide recommendations for improving data quality and accessibility.<br>• Create and maintain documentation for data processes, pipelines, and system architecture.<br>• Implement best practices for data storage and retrieval to maximize efficiency.<br>• Troubleshoot and resolve issues related to data processing and integration.<br>• Stay updated on industry trends and emerging technologies to enhance data engineering solutions.
We are looking for an experienced Senior Data Engineer with a strong background in Python and modern data engineering tools to join our team in West Des Moines, Iowa. This is a long-term contract position that requires expertise in designing, building, and optimizing data pipelines and working with cloud-based data warehouses. If you thrive in a collaborative environment and have a passion for transforming raw data into actionable insights, we encourage you to apply.<br><br>Responsibilities:<br>• Develop, debug, and optimize Python-based data pipelines using frameworks such as Flask, Django, or FastAPI.<br>• Design and implement data transformations in a data warehouse using tools like dbt, ensuring high-quality analytics-ready datasets.<br>• Utilize Amazon Redshift and Snowflake for managing large-scale data storage and performing advanced querying and optimization.<br>• Automate data integration processes using platforms like Fivetran and orchestration tools such as Prefect or Airflow.<br>• Build reusable and maintainable data models to improve performance and scalability for analytics and reporting.<br>• Conduct data analysis and visualization leveraging Python libraries such as NumPy, Pandas, TensorFlow, and PyTorch.<br>• Manage version control for data engineering projects using Git and GitHub.<br>• Ensure data quality through automated testing and validation processes.<br>• Document workflows, code, and data transformations following best practices for readability and maintainability.<br>• Optimize cloud-based data warehouse and lake platforms for performance and integration of new data sources.
<p>We’re seeking a Senior AI/ML Engineer to build and scale real-time data pipelines, drive platform reliability, and lead core AI/ML engineering initiatives. You’ll work across teams to deliver high‑performance, secure, and cost‑efficient data and machine learning systems.</p><p><br></p><p>Responsibilities:</p><ul><li>Architect and maintain scalable data pipelines (GCP, Kafka, Flink).</li><li>Own reliability, observability, and performance of the data/ML platform.</li><li>Optimize infrastructure performance and cloud costs.</li><li>Standardize data modeling and testing (dbt or similar).</li><li>Implement Infrastructure as Code and automation best practices.</li><li>Ensure security, governance, and compliance across data systems.</li><li>Lead cross-functional initiatives and mentor engineering peers.</li><li>Drive continuous improvement in tools, processes, and standards.</li></ul><p><br></p><p><br></p>
Key Responsibilities:<br><br>· Design, develop, and maintain scalable backend systems to support data warehousing and data lake initiatives.<br><br>· Build and optimize ETL/ELT processes to extract, transform, and load data from various sources into centralized data repositories.<br><br>· Develop and implement integration solutions for seamless data exchange between systems, applications, and platforms.<br><br>· Collaborate with data architects, analysts, and other stakeholders to define and implement data models, schemas, and storage solutions.<br><br>· Ensure data quality, consistency, and security by implementing best practices and monitoring frameworks.<br><br>· Monitor and troubleshoot data pipelines and systems to ensure high availability and performance.<br><br>· Stay up-to-date with emerging technologies and trends in data engineering and integration to recommend improvements and innovations.<br><br>· Document technical designs, processes, and standards for the team and stakeholders.<br><br><br><br>Qualifications:<br><br>· Bachelor’s degree in Computer Science, Engineering, or a related field; equivalent experience considered.<br><br>· Proven experience as a Data Engineer with 5 or more years of experience; or in a similar backend development role.<br><br>· Strong proficiency in programming languages such as Python, Java, or Scala.<br><br>· Hands-on experience with ETL/ELT tools and frameworks (e.g., Apache Airflow, Talend, Informatica, etc.).<br><br>· Extensive knowledge of relational and non-relational databases (e.g., SQL, NoSQL, PostgreSQL, MongoDB).<br><br>· Expertise in building and managing enterprise data warehouses (e.g., Snowflake, Amazon Redshift, Google BigQuery) and data lakes (e.g., AWS S3, Azure Data Lake).<br><br>· Familiarity with cloud platforms (AWS, Azure, Google Cloud) and their data services.<br><br>· Experience with API integrations and data exchange protocols (e.g., REST, SOAP, JSON, XML).<br><br>· Solid understanding of data governance, security, and compliance standards.<br><br>· Strong analytical and problem-solving skills with attention to detail.<br><br>· Excellent communication and collaboration abilities.<br><br><br><br>Preferred Qualifications:<br><br>· Certifications in cloud platforms (AWS Certified Data Analytics, Azure Data Engineer, etc.)<br><br>· Experience with big data technologies (e.g., Apache Hadoop, Spark, Kafka).<br><br>· Knowledge of data visualization tools (e.g., Tableau, Power BI) for supporting downstream analytics.<br><br>· Familiarity with DevOps practices and tools (e.g., Docker, Kubernetes, Jenkins).
<p>We are looking for a skilled and innovative Data Engineer to join our team in Grove City, Ohio. In this role, you will be responsible for designing and implementing advanced data pipelines, ensuring the seamless integration and accessibility of data across various systems. As a key player in our analytics and data infrastructure efforts, you will contribute to building a robust and scalable data ecosystem to support AI and machine learning initiatives.</p><p><br></p><p>Responsibilities:</p><p>• Design and develop scalable data pipelines to ingest, process, and transform data from multiple sources.</p><p>• Optimize data models to support analytics, forecasting, and AI/ML applications.</p><p>• Collaborate with internal teams and external partners to enhance data engineering capabilities.</p><p>• Implement and enforce data governance, security, and quality standards across hybrid cloud environments.</p><p>• Work closely with analytics and data science teams to ensure seamless data accessibility and integration.</p><p>• Develop and maintain data products and services to enable actionable insights.</p><p>• Troubleshoot and improve the performance of data workflows and storage systems.</p><p>• Align data systems across departments to create a unified and reliable data infrastructure.</p><p>• Support innovation by leveraging big data tools and frameworks such as Databricks and Spark.</p>
