Top Data Management Jobs

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

Lead data strategy, architecture, and modeling for high-volume transactional network platforms. Build monitoring and anomaly-detection frameworks, optimize operational data schemas, align local assets with enterprise data strategy, communicate findings to stakeholders, and mentor technical staff.

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

Manages research data acquisition, licensing, vendor relationships, contracts, data use agreements, governance, and compliance. Leads data safety reviewers, assesses privacy and contractual risks, develops SOPs and access workflows, trains researchers, and coordinates with faculty, vendors, legal counsel, procurement, compliance offices, and university stakeholders.

Leads data engineering and data science teams, setting strategy and delivering scalable pipelines, data architecture, models, analytics infrastructure, and data governance. Partners with product, analytics, and business stakeholders to prioritize initiatives, assess upstream changes, maintain data quality, and support Snowflake-based warehousing. This hands-on leadership role includes mentoring staff, contributing to technical codebases, and advancing data science and engineering solutions.

Lead and mentor data engineering and DBA teams while driving GCP-based streaming and batch data platform initiatives. Oversee BigQuery, dbt, Apache Flink or Dataflow, data quality, testing, observability, governance, reliability, and cloud cost optimization. Remain hands-on with coding, code reviews, architecture, and complex system problems while aligning data infrastructure with business and product goals. Champion AI-assisted engineering and automation across the platform.

Lead the data engineering squad and oversee the DBA team while driving GCP-based streaming and batch infrastructure projects. Build and review code, establish standards for data quality, testing, observability, governance, and cost optimization, and align data platforms with business goals. The role requires expertise in GCP, BigQuery, dbt, Apache Flink or Dataflow, relational databases, AI-assisted engineering, and team leadership.

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

The Manager, Data Analysis will lead a team of analysts, leveraging analytical skills and models to drive data strategy and improve customer experiences. Responsibilities include mining complex data, enhancing operational efficiencies, and mentoring junior team members while collaborating across business units.

Leads the Enterprise Data Platform team, managing data engineers and driving the data engineering roadmap. Oversees scalable pipelines, ETL/ELT workflows, cloud architectures, data models, governance, quality, lineage, and performance optimization. Partners with technology and business leaders to deliver enterprise data solutions and AI/ML capabilities. Responsibilities include architecture decisions, team development, mentoring, stakeholder collaboration, compliance, and operational improvement.

Leads a data analytics organization supporting enterprise and program data strategies. Builds and mentors data engineering and science teams, deploys predictive and descriptive analytics solutions, manages data infrastructure and automation, establishes visualization and reporting standards, and partners with stakeholders to solve operational problems. The role also oversees UI/UX consistency, data lifecycle management, and adoption of data-driven decision-making practices.

Manages enterprise data lifecycle, governance, integration, interoperability, repositories, and quality processes. Maintains data standards, metadata, validation rules, documentation, and configuration controls while reviewing engineering artifacts for traceability and version control. Collaborates with technical and stakeholder teams to improve data accessibility, reliability, architecture, and operational efficiency, and communicates recommendations through reports, briefings, and technical documentation.

Partners with Product leaders to solve ambiguous business problems through forecasting, modeling, segmentation, cohort analysis, scenario analysis, dashboards, and executive insights. Owns analytical initiatives from problem framing through implementation and measurable outcomes. Uses SQL across large enterprise datasets and applies generative AI and LLM tools to analyze structured and unstructured data, while validating AI-generated outputs. Prioritizes analytics requests, improves recurring workflows, and communicates recommendations to senior stakeholders.

Lead the data engineering squad and oversee the DBA team while remaining hands-on with platform projects. Drive streaming and batch infrastructure using GCP, BigQuery, dbt, and Apache Flink or Dataflow. Establish standards for data quality, testing, observability, governance, documentation, and cloud cost optimization. Promote AI-native engineering practices, ensure transactional database reliability, mentor engineers, and align data platforms with business and product goals.

Own pricing, yield, monetization, retention, and churn analytics for a B2B marketplace. Build supplier yield scores, pricing models, dashboards, predictive churn models, cohort analyses, and A/B tests. Partner with product, operations, engineering, sales, finance, and customer success leaders to translate marketplace data into revenue and retention improvements. Develop production machine-learning models and communicate insights to technical and non-technical stakeholders.

Own supplier-side pricing, yield, monetization, retention, and churn analytics for a B2B marketplace. Build predictive models, dashboards, data models, pricing frameworks, cohort analyses, and A/B tests. Partner with product, operations, engineering, sales, finance, and customer success leaders to identify revenue opportunities, optimize advertising and incentive programs, improve supplier retention, and translate complex marketplace dynamics into actionable business decisions.

Owns governance, quality, standards, and lifecycle management for eight master data domains across ERP and related systems. Administers NetSuite master data, defines validation and error-proofing controls, resolves data discrepancies, maintains audit-ready documentation, and reports quality KPIs. Partners with IT, Supply Chain, Finance, Commercial, Regulatory, Customer Care, and other teams on integrations, migrations, product launches, compliance, serialization, and pricing. Provides cross-functional guidance and drives data discipline without direct authority.

Leads data analytics and data quality for Airbus’s Mobile final assembly facility. Manages the local data portfolio, defines data products and standards, drives data lifecycle improvements, and conducts advanced analyses using AI, machine learning, and predictive models. Translates findings into business insights, establishes KPIs, mentors analysts, supports internal tool development, and coordinates operational recovery plans. The role requires collaboration across manufacturing, process improvement, and leadership teams.

Leads data governance for acquired-company integrations, embedding governance, ownership, quality, metadata, lineage, retention, privacy, legal hold, and compliance requirements across structured and unstructured data. Establishes data inventories, stewardship models, quality controls, retention schedules, and approval processes; coordinates with business, technology, legal, risk, privacy, and security stakeholders. Supports migration, archival, modernization, analytics enablement, governance tooling, executive reporting, and cross-functional transformation readiness.

Leads enterprise HR analytics and business intelligence strategy, including dashboards, reporting, data governance, data quality, automation, and actionable insights. Manages analytics priorities, projects, stakeholders, and deliverables while partnering with HR, IT, and business leaders. Oversees reporting standards, compliance reporting, data integrity, and analytics solutions. Mentors analytics staff and trains end users on data literacy, reporting tools, visualization, and consistent analytics practices.

Lead validation of enterprise-wide analytical tools for risk management: plan and execute validation projects, assess methodology quality and tool risk, prototype best practices, communicate findings, and coach junior staff.

Lead the enterprise master data management and governance strategy across Customer, Product, Asset, and Vendor domains. Build governance models, improve data quality through AI and automation, establish lineage and metadata standards, integrate data across ERP, CRM, PLM, and analytics platforms, and lead data stewardship teams. Own program delivery, budgets, executive reporting, and stakeholder alignment across business and technology functions.

Owns business intelligence and data management for investment operations, developing Power BI dashboards, DAX and Power Query models, Snowflake reporting data, and secure data access. Leads strategic business initiatives, workflow improvements, technology enhancements, AI and LLM automation, stakeholder reporting, vendor coordination, requirements gathering, and project execution. Serves as the subject matter expert for data, reporting, client portals, metrics, and internal technology initiatives.

Leads regional data analytics delivery for Global Business Services, including advanced analysis, reporting, dashboards, KPI frameworks, data governance, and executive decision support. Provides indirect leadership to analysts, establishes analytical standards, supports procurement and sourcing initiatives, evaluates supplier proposals, drives automation and continuous improvement, manages third-party analytics platforms, and develops training to improve adoption and analytics maturity.