We are looking for a Systems Administrator to support daily technology operations for a transport-focused environment in Fort Worth, Texas. This role is responsible for keeping user access, endpoint systems, and core infrastructure running smoothly while delivering responsive support to employees across the site. The ideal candidate brings a practical, hands-on approach to troubleshooting, communicates clearly with end users, and works effectively with broader IT teams to resolve complex issues.<br><br>Responsibilities:<br>• Manage the creation, modification, and removal of user accounts and access rights across a range of business applications.<br>• Deploy, configure, relocate, and update computer hardware and software to meet operational needs.<br>• Diagnose and resolve technical issues affecting desktops, peripherals, applications, and other end-user systems.<br>• Maintain accurate incident records, document work performed in detail, and track time consistently within support tickets.<br>• Escalate unresolved or higher-impact issues to appropriate internal teams and follow through to completion.<br>• Partner with employees and corporate IT groups to address advanced technical concerns and ensure effective communication throughout the support process.<br>• Perform routine system upkeep, including software installations, patching activities, equipment replacement planning, and secure device retirement.<br>• Support identity and permissions administration, backup-related activities, disaster recovery testing, and assigned project-based tasks.<br>• Provide basic telecom, network, and connectivity troubleshooting to help maintain reliable site operations.
We are looking for a Data Engineer to join a Financial Services team in Plano, Texas on a contract basis with the potential for a permanent role. This role is focused on designing and delivering reliable data pipelines in a cloud-first environment, with Snowflake serving as a central platform for analytics and data consumption. The position offers a balanced mix of new development and targeted optimization, with an emphasis on improving data quality, operational visibility, and scalable processing capabilities.<br><br>Responsibilities:<br>• Design, build, and deploy end-to-end data pipelines with Snowflake as a primary data platform.<br>• Create new ingestion and transformation workflows while resolving issues affecting existing pipeline performance and reliability.<br>• Support streaming data integration using Apache Kafka to enable timely and scalable data movement.<br>• Strengthen observability across data workflows by improving monitoring, alerting, and pipeline transparency.<br>• Enhance data quality practices through validation, testing, and proactive issue identification.<br>• Modernize data architecture by reducing dependency on legacy processes and addressing technical debt.<br>• Contribute to engineering standards by applying disciplined development practices, code quality measures, and repeatable delivery methods.<br>• Help expand CI/CD and testing capabilities by promoting more consistent automation across build and release activities.<br>• Use AI-assisted development tools to accelerate coding, testing, and documentation where appropriate.
We are looking for a Data Engineer to join a growing team and contribute to the delivery of reliable, analytics-ready data solutions. This contract opportunity with potential for a permanent role is ideal for someone who enjoys building scalable data pipelines, improving data models, and partnering with technical and business stakeholders to support reporting, self-service analytics, and data science. The role offers the chance to work hands-on with Databricks, Python, PySpark, SQL, and modern data engineering practices in a collaborative environment focused on quality and performance.<br><br>Responsibilities:<br>• Build, maintain, and enhance data pipelines that support dependable data availability for analytics and reporting needs.<br>• Collaborate with data engineering leaders to troubleshoot defects, resolve pipeline issues, and improve overall platform stability.<br>• Develop transformation logic using Python, PySpark, SQL, and Databricks to prepare clean, usable datasets for downstream consumers.<br>• Design and refine data models that improve usability, consistency, and performance across reporting and analytical workloads.<br>• Apply layered data architecture principles, including Bronze, Silver, and Gold structures, to organize and manage data effectively.<br>• Establish and follow engineering standards for validation, testing, monitoring, and documentation to strengthen data quality and maintainability.<br>• Optimize processing and query performance to support efficient data delivery at scale.<br>• Work with business and technical partners to translate data needs into practical engineering solutions that support trusted insights.
We are looking for a Data Scientist to join a healthcare-focused analytics team in Texas, where you will turn complex data into practical insights and scalable solutions. This contract position with the potential to become permanent is ideal for someone who combines strong statistical knowledge with curiosity, business acumen, and a passion for solving meaningful problems. You will work closely with technical and business partners to design predictive models, improve data quality, and communicate findings that support informed decision-making.<br><br>Responsibilities:<br>• Transform large, complex datasets into actionable insights by exploring trends, identifying patterns, and uncovering opportunities that support business goals.<br>• Build, test, and refine machine learning models and predictive solutions that improve decision-making and deliver measurable value.<br>• Prepare structured and unstructured data for analysis through cleansing, validation, and preprocessing to ensure reliability and usability.<br>• Strengthen data acquisition practices by recommending improvements that capture the information needed for advanced analytics initiatives.<br>• Partner with business leaders, analysts, and IT teams to define problems, evaluate options, and shape data-driven strategies.<br>• Communicate analytical findings through clear narratives, presentations, and visualizations that make complex results easy to understand.<br>• Create impactful dashboards and visual tools that highlight performance gaps, emerging opportunities, and areas for operational improvement.<br>• Facilitate discussions with stakeholders to gather requirements, iterate on analytical approaches, and align solutions with business needs.<br>• Handle sensitive information with discretion while supporting a culture of continuous improvement, accountability, and evidence-based decision-making.
<p>We are seeking a hands-on Cloud Infrastructure Engineer to support, manage, and optimize infrastructure across multi-cloud and on-premises environments. This role will work with AWS, Microsoft Azure, Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI), supporting day-to-day cloud operations, infrastructure provisioning, performance, security, connectivity, capacity management, and automation.</p><p><br></p><p>The ideal candidate has a strong traditional IT infrastructure foundation combined with hands-on cloud experience. This person should be comfortable working across multiple cloud platforms rather than being limited to a single provider.</p><p><br></p><p>Key Responsibilities</p><ul><li>Provision, configure, manage, and decommission virtual machines, containers, storage, networking, and other cloud resources.</li><li>Support infrastructure across AWS, Azure, GCP, and OCI environments.</li><li>Establish and maintain asset tagging and resource organization standards to support inventory management, reporting, governance, and cost visibility.</li><li>Monitor cloud infrastructure performance and troubleshoot availability, utilization, and performance issues.</li><li>Perform resource optimization and right-sizing based on capacity, utilization, performance, and business requirements.</li><li>Configure new cloud environments for departments and business units, including resource organization, networking, access, security, and governance.</li><li>Apply general cloud security best practices, including identity and access management, permissions, network security, and resource protection.</li><li>Support and troubleshoot VPNs, networking, DNS, routing, and connectivity between cloud and on-premises environments.</li><li>Provide infrastructure-level support to development teams, including troubleshooting issues involving APIs, authentication, connectivity, and cloud services.</li><li>Perform capacity planning, utilization monitoring, and infrastructure reporting across cloud environments.</li><li>Support both Windows and Linux infrastructure.</li><li>Identify repetitive administrative processes and automate routine infrastructure tasks.</li><li>Develop scripts and automation using technologies such as PowerShell, Bash, and Python.</li><li>Troubleshoot infrastructure issues spanning cloud, networking, operating systems, and applications.</li><li>Maintain documentation of cloud configurations, processes, procedures, and infrastructure standards.</li></ul><p><br></p>
<p>Seeking a hands-on Data Platform Engineer to build and operate the AWS infrastructure supporting an enterprise analytics environment. This is an engineering-focused position centered on <strong>building pipelines, orchestration, and cloud infrastructure</strong>, not dashboards or business analysis.</p><p><br></p><p>What You'll Do</p><ul><li>Build and maintain an AWS-based data platform and Amazon Redshift environment.</li><li>Code and build data pipelines using Python, dbt, and AWS Lambda.</li><li>Work across AWS services including S3, Glue, Step Functions, IAM, and CloudWatch.</li><li>Develop ETL/ELT processes and data transformation workflows.</li><li>Monitor pipeline health and troubleshoot failures, latency, and infrastructure issues.</li><li>Build for reliability, scalability, security, and cloud cost efficiency.</li><li>Support data ingestion into the warehouse environment.</li><li>Maintain data-flow documentation and operational runbooks.</li><li>Translate analytics requirements into technical pipeline and infrastructure solutions.</li><li>Recommend automation and architectural improvements as the platform grows.</li></ul>