Top Data Management Jobs

Manage Data Manufacturing teams responsible for data operations, oversee project management, establish departmental objectives, and develop senior level staff.

Lead a CX analytics team to solve complex business problems using advanced analytics, modeling, and data visualization. Mentor analysts, build analytics roadmaps and OKRs, communicate insights to senior leaders, and operationalize repeatable analytics to free bandwidth for high-value work.

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

As a Curriculum Manager, you will manage the content development lifecycle, collaborate with instructors, and improve data science curriculum, ensuring technical accuracy and pedagogical effectiveness.

Lead and architect the Microsoft Fabric platform; manage a BI and data engineering team; deliver Power BI reporting, data integration, lakehouse/warehouse solutions; build pipelines, Python transformations, and ML models; enforce governance, CI/CD, and capacity management while partnering with stakeholders and data governance.

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 North America marketing analytics product portfolio, evolve MMM to causal and AI-native methods, prioritize roadmap and epics, oversee data engineers and scientists, drive adoption and value measurement for marketing effectiveness.

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 a team to design and deliver enterprise data management, ETL, reporting, low-code apps, and automation solutions. Develop roadmaps, governance for data, reporting, automation and AI, partner across IT and business units, prioritize and deliver process improvements, and ensure scalable, secure analytics and automation practices.

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 backend data operations and ensure reliable flows of student demographic and assessment data into the data warehouse. Build and maintain SQL processes, dashboards, and reports; investigate data quality issues; support internal and external data requests; manage data access and collaborate with stakeholders to translate data into actionable insights.

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.

Manage and improve school data systems and protocols (PowerSchool, SWIS), configure reports, define operational metrics, perform cross-system analysis, produce scheduled and ad-hoc reports, develop training and SOPs, and coordinate with leadership and compliance teams to improve operations.

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 data-driven analyses supporting M&A and private equity transactions. Clean, combine, model, and visualize large financial, customer, pricing, and operational datasets using Python, Alteryx, SQL, and BI tools. Deliver insights on revenue, margin, profitability, and value-creation opportunities, manage client deliverables, mentor juniors, and support business development and proposals.

Lead development and evolution of a scalable data platform, partner with technical and business leaders, define technical vision and governance, drive transformational change, build and manage a high-performing data engineering team, and deliver data capabilities for BI, analytics, and ML.

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.