Top Data Management Jobs in Dallas, TX

Lead design and build of a cloud-based data platform; manage and mentor data engineering staff; define engineering standards, data governance, and access controls; partner with stakeholders to deliver scalable, reliable data pipelines and platform services for analytics and AI.

This role involves leading the Data Engineering team, managing large-scale data pipeline delivery, ensuring data quality, and fostering partnerships with other teams for data governance and project management.

Manage IT teams in the design, development, testing, and implementation of applications, ensuring data integrity and project success while overseeing budgets and team performance.

Manage data analytics efforts across Operations: triage and root-cause data issues, partner with engineering/data/customer success to implement solutions, scope and execute analytical requests, produce reports and dashboards, and communicate findings to technical and non-technical stakeholders.

Lead and hands-on manage data engineering and API teams to design, build, and migrate enterprise-scale cloud data pipelines and APIs. Drive Spark (PySpark/Scala) development, Spark on Kubernetes, Databricks/Snowflake data platforms, AWS integrations, CI/CD/GitOps, and secure hybrid connectivity. Mentor engineers, enforce code quality, optimize cloud costs, ensure compliance (GDPR, CCPA, SOC2), and align technical roadmaps with business objectives.

Manage Finance-focused data products, collaborating with teams to define requirements and drive delivery for financial analysis and reporting.

Technical manager responsible for designing, building, and operating an enterprise Lakehouse on Azure. Leads data and analytics engineers, defines architecture and governance (Unity Catalog), ensures data quality, SLAs, DevOps/CI-CD, and delivers self-service analytics with Power BI.

Lead end-to-end delivery of data platform engagements: design and implement scalable ingestion and transformation pipelines, write and review production code (Python/SQL/Scala/Spark), architect cloud environments, advise clients, manage and mentor teams, and support practice development and business development activities.

As a Senior Data Steward Manager, you'll oversee data management and governance, ensure data quality, and work with cross-functional teams to meet data standards.

Lead master data management governance, define standards and mappings, approve data changes, audit mappings, manage a team of mapping specialists, collaborate with stakeholders, and drive MDM project delivery and training.

The Senior Manager of Data Engineering will lead a team, manage data platforms, drive modernization, oversee budgets, and ensure data solutions are scalable and reliable.

Lead enterprise data governance by defining operating models, policies, stewardship, MDM, metadata, lineage, quality KPIs, and controls. Partner cross-functionally to enable analytics, AI readiness, ERP/PIM/CRM integrations, run governance councils, drive remediation, and communicate executive reporting to improve data trust and decision confidence.

Lead a small data engineering team partnering with Engagement Marketing to build scalable ETL/ELT pipelines, ensure data quality, define marketing metrics, integrate trusted data with ad platforms, and drive the data roadmap to enable measurement and growth.

Lead and execute end-to-end ERP data migrations into Dynamics 365 (F&O and CE) for acquisitions. Define migration strategy, design and run ETL, data mapping, reconciliation, validation, and cutover. Manage a blended team, ensure data quality and governance, and drive automation and continuous improvement across migration processes.

Lead a Salesforce data engineering team to design, deliver, and support Salesforce-to-Salesforce integrations and migrations, data modeling, ETL/transformations, automation, and observability. Manage hiring, performance, and career development; partner with stakeholders; adopt AI/LLM agent tooling to automate workflows and improve data quality; reduce technical debt and document systems and processes.

Lead a hands-on data engineering team to build and scale production data pipelines, datasets, and observability for alternative-data products. Drive architecture, data modeling, QA, and AI-ready dataset design while coaching engineers, partnering with product and research, and owning operational excellence across Databricks, Airflow, SQL, and PySpark.

Manage CVS Health's data partnerships and monetization strategy, source new partnerships, ensure operational success, and drive data product adoption across analytics teams.

Serve as the analytics bridge between marketing/operations and data teams: translate business questions and KPIs into clear product requirements, own delivery of treated tables, semantic layers, reports and dashboards, align stakeholders on a single source of truth, run gap analyses, document processes, and ensure delivered data products drive decision-making and adoption.

Lead enterprise data strategy and governance, build AI-ready data infrastructure and BI systems, own SharePoint platform, partner cross-functionally to ensure data quality, access, compliance, and user adoption.

The Master Data Manager will develop data strategies, manage workflows, enhance data quality, and lead data management teams to achieve business goals.

Manage day-to-day execution of regional assessment builds and readiness operations in Renaissance (Illuminate) DnA, maintain data quality and compliance, coordinate vendor data collection, develop documentation and training, support regional stakeholders, and continuously improve assessment and data workflows to ensure timely, accurate reporting.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experimentation insights; manage people, mentor staff, partner with product and engineering, and build accessible data products and measurement practices.

Own and scale the finance and accounting data ecosystem: design and maintain BigQuery integrations, ensure data integrity and governance, build reconciliations and automated controls, develop scalable reporting and dashboards, support monthly close, forecasting, budgeting, and automate finance processes to improve visibility and efficiency.