Top Data & Analytics Jobs

Design, build, and optimize data pipelines and architecture; extend ML platform; implement ETL using SQL, Python, and AWS; build analytics tools; supervise and mentor junior data engineers; collaborate with development and analytics teams to support data-driven products.

Lead a team to develop and execute data analytics strategy for aerospace finance operations. Build data pipelines, apply statistical and advanced analytics, create dashboards, collaborate cross-functionally, and drive process improvements and cost savings while ensuring data quality and mentoring analysts.

The Data Engineer will design and build scalable data systems, contribute to the architecture of the data platform, and collaborate with AI/ML engineers to enhance automation and intelligence in Canoe's systems.

The Staff Data Engineer will lead design and implementation of analytics platforms and data products, collaborate cross-functionally, mentor engineers, and drive best practices at Upside.

Develop, curate, and publish authoritative geospatial data products in ArcGIS Portal; build Python data-processing pipelines; and create Tableau dashboards and web maps. Manage metadata, hosted feature layers, and data discoverability while partnering with mission users to transform large spatial and tabular datasets into operational visualizations and automated workflows.

As a Mid-level Applied AI Data Scientist, you will apply statistical methods and machine learning to derive business insights from data and create Tableau visualizations.

The Senior Analytics Engineer will manage the analytics layer, owning dbt projects, orchestrating data pipelines, defining metrics, and ensuring data quality while mentoring the data team.

Senior analytics leader who defines analytic strategy, leads a team of SQL analysts and BI developers, architects scalable frameworks for medical economics, risk, population health and value-based care, ensures methodological rigor in DBT/Spark and Quicksight dashboards, drives automation and AI integration, presents to executive stakeholders, and mentors senior analytic talent.

Own and build canonical data models and metric definitions using dbt and cloud warehouses. Create tests, documentation, lineage, and data quality checks; reconcile metrics across teams and payer customers; partner with analysts, data scientists, product, engineering, and finance; optimize warehouse performance, cost, and PHI-aware access patterns.

Lead and grow a Business Intelligence team, partner with senior leaders to prioritize analytical initiatives, ensure analytic output quality, drive BI operating model evolution, adopt modern BI tooling and self-service, and embed AI-assisted methods to improve decision-making.