Top Senior Data Management Jobs

Leads the design, delivery, and reliability of an enterprise data platform. Manages and mentors data engineers, oversees architecture and scalable pipelines, establishes engineering standards, and drives platform modernization. Responsibilities include incident response, monitoring, governance, security, AI-assisted development, automation, and GCP cost optimization. The role requires hands-on technical leadership across data modeling, cloud infrastructure, CI/CD, batch and streaming architectures, and stakeholder collaboration.

Leads data strategy and analytics for the Risk/Credit team, translating complex datasets into insights for Credit, Operations, Marketing, Product, and Finance. Responsibilities include automating Python/R workflows, building Tableau dashboards, partnering with Data Engineering on Databricks workflows, conducting strategic analyses, monitoring data quality, presenting recommendations to leadership, and documenting analytical methodologies. The role requires strong SQL, cloud data warehouse, visualization, analytics programming, distributed computing, and version-control expertise.

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.

Leads data and analytics consulting teams delivering enterprise data architecture, pipelines, analytical environments, data models, visualizations, and integrations. Responsibilities include hands-on SQL and Python development, project lifecycle leadership, stakeholder workshops, executive communication, risk mitigation, client support, mentorship, recruitment, and practice growth.

Establishes and operates North America Operations’ data-governance framework, including ownership, stewardship, quality, metadata, lineage, definitions, and AI governance. Partners with business, data, technology, risk, and compliance teams to resolve data issues, automate controls, improve trust, and embed governance into data products, analytics, and AI solutions. Develops playbooks, training, metrics, and continuous-improvement processes while driving accountability across functions.

Leads the data platform strategy, infrastructure, operations, and continuous improvement programs. Manages data engineers, provides technical guidance through design and code reviews, oversees data pipelines and incidents, drives observability and automation, coordinates enterprise AI and analytics initiatives, and manages team budgets and schedules. The role also supports data governance, platform technology selection, scalable solution design, and evolving team capabilities.

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.

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.

Leads cross-functional data management and analytics projects for pharmaceutical and life sciences clients. Responsibilities include data warehouse development, ETL and schema design, data analysis, process optimization, client communication, project management, business development, and mentoring junior staff. The role also provides strategic guidance, develops reporting solutions, manages timelines and resources, and contributes to internal data platform initiatives.

Leads Sensient’s global Business Intelligence practice and data strategy. Oversees BI, data warehousing, enterprise reporting, IT infrastructure, and reporting capabilities. Advises senior leadership, manages technology selection and implementation, coordinates infrastructure priorities, supports contract negotiations, and drives continuous improvement. The role leads IT teams and collaborates globally to turn complex data into actionable business insights while ensuring systems meet organizational needs, budgets, and timelines.

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.

Leads Data Operations, including reporting, dashboards, data warehouse and dbt model oversight, data quality, governance, service levels, incident response, and stakeholder prioritization. Manages and develops data professionals while partnering with Data Engineering, Security, Privacy, Compliance, and Enterprise Architecture. Ensures reliable, secure, well-documented data services and protects PHI through appropriate access, privacy, lineage, retention, and monitoring controls.

Lead and develop a team of Data Analysts while overseeing analytics projects, reporting, data governance, and self-service BI solutions. Partner with engineers, data scientists, and business leaders to establish trusted datasets, improve data quality, communicate metrics, and advance predictive analytics and AI-enabled decision support. Coach technical and non-technical staff in statistical methods and data literacy, evaluate modern analytics technologies including Microsoft Fabric, and drive insights that improve manufacturing performance, quality, and operational efficiency.

Leads research, data analysis, reporting, and data management for film and media incentive programs. Oversees data collection, validation, database maintenance, reporting systems, program evaluation, and industry research. Prepares executive briefings, reports, spreadsheets, and actionable recommendations; tracks production status and incentive structures; improves workflows and data quality; and supports strategic planning, policy analysis, stakeholder engagement, and cross-functional initiatives.

Leads client-facing data and analytics projects involving data modernization, governance, business intelligence, automation, systems integration, and process improvement. Translates business needs into technical requirements; designs data pipelines, warehouses, dashboards, APIs, and workflow solutions; implements quality and governance controls; manages projects through adoption; and mentors team members while supporting client relationships and business development.

Leads and scales a global data engineering and analytics team while remaining hands-on with architecture, pipelines, data quality, dimensional modeling, dashboards, reporting, and customer-facing deliverables. Owns the analytical data platform supporting clinical, operational, product, financial, and customer data. Partners with cross-functional stakeholders, investigates complex data issues, improves platform reliability and security, and mentors engineers.

Leads Criminal and Housing Data Acquisition teams, overseeing vendors, data quality, compliance, staffing, KPIs, audits, training, reporting, and process improvement. Resolves escalated data issues, expands public-record coverage, and provides operational guidance while partnering with the Director of Data Acquisition. The role requires SQL Server, XML, HTML, reporting, criminal-record lifecycle, and team-supervision experience. Work is remote within the United States or office-based in Cleveland, with occasional overnight travel.

Leads and coaches a data engineering team while contributing hands-on to platform architecture, data modeling, ETL pipelines, data quality, and analytics solutions. Designs trusted facts, dimensions, snapshots, and slowly changing dimensions using Snowflake, Databricks, dbt, and Airflow. Partners with stakeholders, security teams, vendors, and cross-functional groups on data strategy and controls, resolves production issues, supports incident response, and develops engineering talent.

Manage secure, compliant data environments, including governance policies, data architecture, integration, quality, security controls, audits, and performance optimization. Lead data analysis, reporting, documentation, and cross-functional collaboration while mentoring junior staff. The role requires protecting sensitive or classified data, maintaining access controls and encryption, and ensuring compliance with government and organizational standards.