Top Senior Data & Analytics Jobs

Lead design and delivery of scalable data pipelines and APIs for Digital Risk Protection. Mentor engineers, align and ingest multiple data streams (including graph data), productize analytics and LLM outputs, and drive DRP technical projects with stakeholders to enable data-driven intelligence.

Lead quantitative UX research for Target's enterprise products: own measurement programs (SUS, Voice of Vendor/Partner, intercepts, benchmarking), design and run large-scale surveys and experiments, perform statistical and driver analyses, develop dashboards and reusable measurement frameworks, partner with cross-functional teams to connect attitudinal and behavioral data, and translate quantitative findings into actionable product and business insights.

Lead the data platform team owning dbt projects, CI/CD, and Snowflake infrastructure. Architect scalable onboarding for new sources, enforce data quality via tests and contracts, review designs, prioritize roadmap, partner with stakeholders, and grow engineers while advancing AI/agent integration.

Lead enterprise analytics architecture and strategy across Epic Cogito, BI tools, and cloud platforms. Design scalable, secure solutions, enforce RBAC and DevOps/CI-CD practices, mentor federated teams, guide tool selection, and ensure alignment with business priorities. Provide architectural oversight, stakeholder consultation, and adoption planning for analytics initiatives in a large healthcare system.

Lead design and scaling of ELT pipelines and analytics schemas on Snowflake. Build Looker views, CI/CD automation, and orchestration workflows (Prefect/Airflow). Ensure production reliability with monitoring (Datadog, Monte Carlo), partner with cross-functional teams, and provide technical leadership including code reviews, testing, and end-to-end ownership of data integrity and platform trustworthiness.

Lead early-stage analytics: explore ambiguous business problems, develop hypotheses, build rapid analytical prototypes, and collaborate with stakeholders and data science teams to translate insights into experiment-ready work and repeatable frameworks supporting publisher partnerships and commercial decisions.

Develop and maintain pricing models and multi-category pricing strategies; analyze market, competitor, and input cost signals; build dynamic tools and automated processes; use statistical modeling to evaluate scenarios; collaborate cross-functionally; validate data and mentor junior analysts to improve pricing effectiveness and decision-making.

Translate business needs into clear data requirements, design and maintain curated integrated datasets, validate mappings and lineage, support data governance and quality, enable data products for reporting and analytics, and lead small data integration and process-improvement initiatives across business, analytics, and engineering teams.

Lead detection, triage, and resolution of processing errors to protect compliance and finances; manage daily error queues; draft technical specifications and test plans; validate and reconcile data using intermediate-to-advanced SQL; maintain documentation and knowledge base; coordinate cross-functional delivery of crop insurance requirements; provide responsive customer support and drive automation/improvement initiatives.

Lead and mentor a data engineering team to architect and implement scalable cloud lakehouse/warehouse solutions, design enterprise data models, build batch and real-time ETL/ELT pipelines, enforce data quality and governance, establish CI/CD and DataOps practices, and enable AI and advanced analytics.