Top Senior Data Management Jobs

Lead enterprise data and analytics governance for a federal technology services program, ensuring secure and effective data usage and decision-making support.

Lead the design, build, and scaling of an enterprise data governance platform integrating Collibra, Snowflake, and Databricks Unity Catalog across multi-cloud and on-prem environments. Define governance frameworks for lineage, metadata, quality, access, and compliance; drive API-driven automation, interoperability standards, and adoption; partner with engineering, risk, and business stakeholders to deliver measurable KPIs, roadmaps, and executive reporting.

Lead and grow a Data Engineering & Analytics team to deliver governed, reliable data products. Own data pipelines, dbt models, BigQuery, Airflow, and Python-based tooling; manage intake/prioritization (Jira); advance analytics from reporting to predictive/prescriptive models; ensure PHI-safe practices, stakeholder alignment, and on-time delivery of reports, invoices, and analytics.

Lead evaluation, development, and deployment of scalable batch and streaming data pipelines and datasets to support ML training/execution and search analytics. Architect end-to-end hardware/software solutions, implement automation, monitor and troubleshoot distributed systems, define standards, mentor ETL developers, and collaborate with data scientists, architects, and operations to ensure security, performance, and reliability.

Lead enterprise data engineering strategy and teams to build scalable, secure cloud data platforms (Snowflake, SQL Server) enabling real-time analytics, AI/ML, migrations, and self-service data. Oversee architecture governance, vendor and budget management, cross-functional stakeholder engagement, agile delivery, code quality, and continuous improvement while developing engineering leadership and succession plans.

Lead combined Analytics Engineering and Data Engineering teams owning the end-to-end data roadmap from ingestion to trusted metrics. Manage hiring and performance, set architecture and platform investments, enforce testing/monitoring/documentation standards, review technical decisions, and partner with product and business stakeholders to translate needs into prioritized deliverables.

Lead enterprise data management including governance, data quality, MDM, cataloging, and controlled distribution. Own policies, stewardship, MDM workflows (Reltio/SAP), vendor relationships, and metrics to improve master data trust, reduce duplicates, and enable faster onboarding. Coach stewards, partner with engineering/BI, and support audit, privacy, and compliance.

Lead MDM policy, processes, and team to ensure accurate, consistent master data. Oversee data mapping, governance, stakeholder collaboration, change approvals, audits, and team training while reporting progress and managing resources.

Lead design, reliability, and daily operations of core data pipelines and analytics infrastructure while managing data and analytics engineers. Ensure scalable ELT/ETL, trusted dbt models, data governance, and cross-functional alignment with Analytics, Product, and Technology. Translate business priorities into technical roadmaps and promote best practices, monitoring, and documentation.

Lead and scale a distributed data engineering organization: design and maintain cloud-native data infrastructure, build ETL/ELT pipelines and event streams, ensure data quality and observability, deliver dashboards and analytics tools, partner with product and business stakeholders, and manage analytics project prioritization and team performance.

Lead daily master data operations and governance, manage MDM tools and integrations, ensure data quality and remediation, establish metrics and SLAs, lead and develop a team, manage vendors, and drive continuous process improvement and stakeholder enablement.

Lead BI, reporting, and data governance for insurance BPS. Manage call center/business managers, build enterprise Power BI solutions, ensure data integrity, drive KPIs, partner with Ops/IT/Finance, and deliver reporting modernization and audit‑ready governance.

The role involves leading data engineering and analytics teams, optimizing data systems, collaborating on data pipelines, and managing data infrastructure projects.

The Data Specialist will manage BIM data integration and digital ecosystem strategies to support the LA28 Olympic Games, focusing on operational readiness and data-driven decision-making.

Lead design and maintenance of scalable data models, dbt transformations, and cloud data warehouses. Manage a distributed team of 7–8 data engineers/analysts, ensure data quality, governance, ELT best practices, performance tuning, integrations, and stakeholder alignment across servicing technology.

The Manager, Data Governance will lead the implementation of data governance strategies to support AI and analytics, ensuring data quality, compliance, and ownership while promoting data literacy across the organization.

Lead data-driven quality initiatives: build analytics, forecasts, dashboards, and automated tools using Power BI, Databricks, SQL, Python and DAX; manage data pipelines, governance, and quality systems; drive cross-functional projects, mentor analysts, and deliver actionable insights to improve product performance and customer satisfaction.

The Data Analytics Manager will collaborate with Commercial Lines leaders, manage the Global Data Warehouse, and drive data insights for effective decision-making.

This role involves leading the Data & AI team, building modern data platforms using Microsoft technologies, overseeing project delivery, and mentoring team members while engaging with clients.

Manage and lead a cross-functional team supporting data and analytics platforms, production pipelines, and applications. Define and track operational KPIs, drive process improvement and automation, manage staff performance and career development, engage with business units, and present results to senior leadership to ensure timely, on-budget delivery of data engineering and operations outcomes.

Lead ESG data governance and controls to produce audit-ready sustainability disclosures. Build and scale impact accounting models, perform reconciliations and variance analysis, partner with Data & Analytics to create dashboards (Tableau, Snowflake), and manage finance-grade reporting for CSRD and IFRS S1/S2 across global teams.

Lead enterprise master data governance and quality across Customer, Material, Vendor, Product, and Business Partner domains. Define strategy, operating model, and roadmap; manage and mentor a team of Master Data Analysts and Stewards; act as SAP MDG/S4HANA subject-matter expert; drive data quality KPIs, automation, stakeholder alignment, and organizational change to embed data stewardship and enable digital transformation.

Lead and grow a data engineering team to design, build, and operate scalable, cost-efficient data lakehouse pipelines and infrastructure. Define technical strategy, enforce engineering best practices (CI/CD, testing, monitoring), own roadmap and capacity planning, collaborate with product and engineering stakeholders, manage on-call and operational automation, and hire talent. Ensure data governance, lineage, and compliance in a regulated healthcare environment.

Lead and implement enterprise data governance across SAP and non‑SAP systems: define frameworks, metadata, lineage, data quality rules, business glossary, and ownership; run workshops, support MDM and compliance, resolve data issues, and deliver Power BI reporting and governance metrics to improve data visibility and decision-making.

Lead data governance for data products by implementing policies, managing the enterprise data catalog, defining data quality rules and SLAs, collaborating with pipeline teams to embed governance, mentoring junior analysts, and maintaining governance documentation to ensure trusted, discoverable, and mission-ready data assets.