Top Senior Data Management Jobs

Manage program data and documentation across the contract lifecycle: compile, review, control, publish, and submit deliverables to meet CDRL/DID requirements. Develop and implement data/configuration management processes, maintain master files, set milestones, report status, and coordinate with stakeholders to ensure timely, compliant deliveries.

The Data Strategy Manager will lead projects to deliver data strategy solutions in Life Sciences, manage client relationships, and mentor team members.

Lead a product management team for enterprise data platform and data governance. Define strategy, roadmaps, and deliverables; manage program/project lifecycles; partner with stakeholders to build cloud and AI-enabled governance capabilities; apply agile methods; ensure regulatory and audit responses; develop and mentor staff.

Lead and mentor a team of analysts to deliver HR-related analytics and BI solutions. Mine and model large datasets, design tests, improve reporting and operational efficiencies, and collaborate across business units to inform strategy and product decisions.

Lead data governance for the Global Payment Network: implement and enforce policies, ensure data quality, master data management tooling, drive automation and process improvements, collaborate with executives, data stewards and tech teams, and synthesize risk reporting and insights for senior leadership.

Lead validation of enterprise analytical tools: refine validation framework, plan and execute projects, assess methodology quality and risk, prototype best practices, communicate findings, and coach junior staff.

Lead a team to design, operate, and scale core data pipelines and analytics infrastructure. Ensure reliable ELT/ETL, dbt-based models, data governance, metric consistency, and cross-functional partnership to deliver trusted self-service analytics and measurable business impact.

Lead a team delivering enterprise-wide model risk reporting and AI-driven automation. Build and deploy scalable ML/AI solutions, conversational reporting, multi-agent workflows, and centralized data integrations. Drive analytics strategy, validate models and data, improve reporting and operational efficiency, and collaborate across business units.

Lead development, deployment, and optimization of cloud data platforms and real-time pipelines. Manage cross-functional on-site and offshore teams, ensure production stability, troubleshoot issues, optimize AWS and data warehouse cost/performance, implement CI/CD for pipelines, and integrate AI-driven ops for anomaly detection and predictive data quality.

Lead and scale a data engineering team to build and maintain BigQuery-based ELT pipelines and Medallion architecture. Provide technical direction, hands-on engineering (dbt, Python, Fivetran), enforce governance, data quality, observability, CI/CD and IaC standards, and partner with platform and business domains to deliver a reliable data platform.

Serve as a second-line data risk advisor by validating enterprise analytical tools, conducting risk and gap assessments, influencing stakeholders, designing controls, leading validation projects, mentoring staff, and ensuring data management practices meet regulatory and enterprise risk standards.

Design, build, and validate SAP MDM repositories and logical data models. Configure MDM clients (console, data manager, import/syndication managers), create import/syndication maps, workflows, matching rules, and DB views; perform CLIX and server-level operations, INI configuration, and interface testing. Liaise with data providers, subscribers, and downstream systems and lead the team.

Lead design and implementation of SAP MDM repositories and data models; configure MDM clients, import/syndication maps, workflows, web services and CLIX operations; develop and test integrations with upstream/downstream systems; produce technical specifications and unit tests; coordinate with data providers and stakeholders.

Lead and grow a data engineering team, define data platform architecture and reliability (warehouse, ingestion, transformations, orchestration), set engineering standards, partner cross-functionally to support analytics and ML, and translate technical decisions for executive stakeholders.

The Senior Manager will lead cross-functional analytics projects, validate analytical tools, and mentor junior staff while driving data-based business strategies.

Lead and grow a Data Governance team to build and run governance programs: metadata standards, taxonomy, glossary migration, data catalog ownership (Atlan), asset certification, data quality observability, and stakeholder adoption. Act as subject-matter expert, enforce certification standards, arbitrate definitions, and apply AI tooling to scale governance work.

Lead a small data engineering team and own market data platforms from ingestion through delivery. Build and maintain KDB+/Q time-series systems, ensure data correctness, low-latency decoding, replay/recovery, and reliable distribution to downstream consumers. Write production code, review designs, improve observability, and prepare the platform for AI-driven consumers.

Lead a team delivering Power Platform and AI-driven analytics solutions (Power BI, Power Apps, Power Automate, Copilot Studio, Snowflake). Guide data modeling, governance, automation, and AI-powered workflows; prioritize initiatives, modernize reporting, and mentor engineers to drive scalable, self-service analytics and business application adoption.

Lead and mentor a data engineering team to design, build, and support scalable ETL/ELT pipelines and cloud data platforms (Snowflake, ADF, Databricks). Define data engineering roadmap, enforce data governance and quality, implement CI/CD and infrastructure-as-code, and collaborate with stakeholders to deliver trusted data for analytics, reporting, automation, and business decision-making.

Lead enterprise analytical tool validation by designing frameworks, executing validation projects, assessing model quality and risk, prototyping best practices, communicating results, and mentoring junior staff. Partner cross-functionally to influence strategy and ensure analytical rigor across large data and open-source tool environments.

Provide Regional Content Management and GEOINT support. Advise on data delivery methods, analyze data for enhancements, and develop workflows. Present instruction on GEOINT usage and maintain map services using ESRI Portal technology.

Lead and grow the data platform engineering team; own technical direction for pipelines, infrastructure, orchestration, and standards; drive reliability, observability, cost optimization, and governance; recruit and mentor engineers; collaborate cross-functionally to align platform priorities with business needs and enable analytics and ML workloads.

Lead the Managing Data Steward team for Small Business Bank to define and execute data management strategy, governance, quality controls, and data product development. Drive adoption of open-source and cloud-native (AWS) technologies, oversee data catalog health, monitor KRI's, manage data issue resolution, and report insights using advanced visualization. Coach and develop a high-performing analytics team while partnering with engineering and enterprise functions to standardize data flows and migrate on-prem systems to cloud.

The Senior Manager of Data Analysis will manage validation projects, assess analytical tool risks, and mentor junior staff while collaborating cross-functionally and enhancing analytical capabilities.

The role involves leading a team to develop AI and ML solutions, manage customer interactions, and analyze large data sets using various technologies.