Top Data Management Jobs

Leads enterprise analytical tool validation, assesses methodology quality and risk, researches emerging analytics practices, executes validation projects, communicates findings, and mentors junior staff. Partners cross-functionally to influence business strategy and develops solutions to complex data and business problems.

Design, build, and support scalable cloud data platforms, pipelines, and applications. Collaborate with Agile teams, product managers, engineers, analysts, and data scientists while applying distributed data, lakehouse, streaming, and full-stack technologies. Develop secure, resilient, and reusable data solutions using Python, Spark, SQL, Databricks, Snowflake, and relational and NoSQL databases. Mentor technical contributors, enforce engineering patterns, communicate outcomes, and support data privacy and access controls.

Design, build, and support scalable cloud data platforms, pipelines, and applications. Develop distributed and streaming data workloads, data models, and warehousing solutions using Python, Spark, Databricks, Snowflake, and relational and NoSQL databases. Establish reusable engineering patterns, security controls, and operational standards while collaborating with product and engineering teams. Mentor data professionals, communicate technical concepts to stakeholders, and deliver resilient data solutions for enterprise use.

Leads data analysis strategy, modeling, reporting, experimentation, and process improvement using large and complex datasets. Manages and mentors junior analysts, collaborates across business units, supports business intelligence initiatives, and contributes to data products, dashboards, testing frameworks, and operational efficiency improvements. The role involves programming, database analysis, strategic project ownership, and stakeholder consultation in a hybrid environment.

Leads enterprise analytical tool validation, assessing methodology quality, technical risks, usage, and opportunities. Plans validation projects, researches emerging analytical practices, prototypes solutions, communicates findings through reports and presentations, and mentors junior staff. The role requires extensive data analysis, open-source data technology development, statistical or econometric modeling, large-scale data analysis, governance, predictive analytics, and people management.

Design, build, and support scalable cloud data platforms, pipelines, and applications. Responsibilities include data modeling, architecture, distributed processing, relational and NoSQL databases, data security, observability, and real-time workloads. The role collaborates with product and engineering teams, establishes reusable engineering patterns, communicates technical concepts, and mentors data professionals while delivering resilient solutions.

Leads a data analytics team comprising data scientists, BI analysts, and AI developers. Provides mentorship, technical oversight, workflow optimization, performance management, stakeholder communication, project prioritization, and governance stewardship. Ensures analytical integrity, data quality, privacy, AI validation, ethical practices, and alignment with organizational goals. Partners with data engineering and executives to translate business needs into technical objectives and actionable insights.

Lead large-scale data engineering initiatives, designing scalable cloud data platforms, pipelines, and architectures. Use Python, Spark, SQL, Databricks, Snowflake, AWS, relational and NoSQL databases to deliver resilient data solutions. Mentor engineers, analysts, and data scientists; establish engineering standards; evaluate platform choices; and collaborate with product and software teams to support enterprise data transformation and AI capabilities.

Leads and coaches a data engineering team supporting finance analytics. Oversees data warehouse, ETL, cloud data management, analytics solutions, and engineering project delivery. Ensures reliable, high-quality pipelines and accurate stakeholder reporting while providing technical guidance, shaping data strategy, and driving cross-functional initiatives with senior leaders.

Lead data analytics for the Hotels Travel Agency team: define KPIs, build dashboards, run A/B tests, conduct deep-dive analyses, troubleshoot tracking and data quality, and partner with product and engineering to improve data models and accessibility.

Manage data analytics for PULSE Risk & Compliance by analyzing large datasets, identifying transaction anomalies and risk exposure, validating models, improving reporting and processes, and supporting compliant data strategies. The role involves Python-based programming, BI, database and data-storage design, strategic testing, cross-functional collaboration, project leadership, and people management in a hybrid environment.

Leads enterprise-wide validation of analytical tools, including planning validation projects, assessing methodology quality and tool risk, researching best practices, and communicating findings through reports and presentations. Partners cross-functionally to influence business strategy, handles concurrent projects, develops solutions to business problems, and coaches junior staff. The role requires substantial data analysis, statistical or econometric modeling, large-scale data manipulation, open-source technology experience, and people management.

Leads data analysis strategy and manages junior analysts while mining large datasets, building and validating models, improving processes and reporting, evaluating products and marketing initiatives, and supporting data and storage system design. The role requires strong programming, business intelligence, data governance, and analytical leadership skills in a financial services environment.

Manages a data analytics team delivering complex analysis, forecasts, reports, dashboards, and business insights. Integrates data from multiple sources, defines data quality standards, audits reporting accuracy, and identifies operational improvements and strategic opportunities. Leads high-visibility projects, develops analytical specifications and presentations, communicates findings to senior management, and coaches team members on analytical quality and methodology.

Manages a data analytics team responsible for complex reporting, forecasts, dashboards, data integration, quality audits, and ad hoc analysis. Uses data trends, modeling, and optimization methods to identify business opportunities and operational improvements. Oversees strategic projects, develops data definitions and reporting specifications, presents insights to senior management, and coaches team members on analytical quality and accuracy.

Leads data analytics strategy, modeling, testing, reporting, and process improvements across business units. Mines complex databases, evaluates products and processes, improves operational efficiency, and consults on data systems. Manages and mentors junior analysts while supporting projects through the full lifecycle. The role emphasizes business intelligence, programming, strategic analysis, and collaboration in a fast-paced environment.

Analyze Medicaid and T-MSIS data to implement CMS payment model functions, including attribution, payment calculations, and quality measurement. Translate policy into specifications, SQL code, analytic files, and documented methodologies. Assess cross-state data quality, link Medicaid and Medicare sources, perform quality assurance, reconcile results, and communicate findings to technical and non-technical audiences. The role also involves code review, knowledge sharing, and supporting federal healthcare consulting engagements.

Leads and develops a team of Data Migration Engineers responsible for moving customer data into SaaS products. Provides technical guidance on SQL, ETL, data mapping, scripts, troubleshooting, and quality control. Manages project priorities, risks, costs, escalations, cross-functional coordination, global handoffs, and weekend coverage. Partners with engineering and operations teams to resolve defects and improve migration processes, tooling, automation, and cloud-based data platforms.

Leads data analysis strategy, modeling, testing, reporting, and process improvements using large-scale databases. Manages and mentors junior analysts, evaluates products and marketing initiatives, improves operational efficiency, consults on data systems, and collaborates across business units. The role requires strong programming, business intelligence, communication, leadership, and project management skills.

Leads a team responsible for data engineering platforms, pipelines, schemas, governance, databases, transformations, data marts, and production operations. Sets technical direction, manages architecture and delivery priorities, mentors and hires engineers, and partners with stakeholders. The role requires hands-on involvement in data platform design, PostgreSQL optimization, orchestration, reliability, security, and analytical data serving. It also manages project plans, staffing, budgets, performance measures, and cross-team technical delivery.

Leads a team of data scientists and BI engineers responsible for demand forecasting, customer routing analytics, budgeting projections, and core business KPIs. Designs scalable Snowflake datasets, metric definitions, and Tableau self-service analytics; partners with Product, Engineering, and Finance; establishes analytical strategy and roadmaps; applies statistical and causal reasoning; and guides responsible AI-assisted analytics practices.

Leads data engineering, data science, and AI initiatives, including Snowflake architecture, ETL pipelines, AWS data systems, data warehousing, analytics, and AI/ML solutions. Manages data governance, dashboards, experimentation, and web analytics integrations while building and mentoring multidisciplinary teams. Partners with Product, Editorial, Engineering, and business stakeholders to translate data needs into scalable solutions and drive business impact.

Leads enterprise analytical tool validation, assessing methodology quality, risk, technical issues, and business impact. Plans validation projects, researches emerging practices, develops solutions, communicates findings through reports and presentations, and mentors junior staff. The role requires extensive data analysis, statistical or econometric modeling, open-source data technology experience, data governance knowledge, predictive analytics expertise, and people management.

Build and operate scalable cloud data platforms and pipelines for Capital One’s Risk Tech organization. Responsibilities include designing distributed data solutions, enforcing engineering patterns, implementing security controls, collaborating across Agile teams, mentoring developers and analysts, and delivering AI-powered risk management products. The role requires expertise in Python, Spark, SQL, databases, cloud data warehousing, data modeling, and pipeline development.

Leads the People data ecosystem, including Snowflake workforce data models, pipelines, governance, metric certification, and data quality. Develops scalable workforce analytics products using Visier and Snowflake, enables governed AI-driven insights, replaces manual reporting with self-service solutions, and manages a high-performing team of data and analytics professionals.