Top Remote Data & Analytics Jobs in Milwaukee, WI

Entefy seeks a Senior Data Scientist with a Master's or PhD in a relevant field, and 3+ years of experience. Responsibilities include delivering advanced analytics, leading teams, and extracting insights from datasets.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

Design, implement, and support enterprise data integrations connecting JDE, Workday, Salesforce and other platforms. Lead SQL-driven ETL/ELT pipelines, develop reusable integration frameworks, ensure data integrity and audit readiness, perform regression and production troubleshooting, and provide architectural oversight and mentorship across multiple concurrent projects.

Design and deliver scalable Power BI data models, dashboards, and reporting solutions. Collaborate with stakeholders, establish visualization governance and best practices, prototype solutions, and own projects end-to-end to enable data-driven decisions across healthcare teams.

The Staff Data Analyst will enhance data usage for strategic decisions, architect scalable models, partner across teams on data solutions, and lead analytics engineering standards.

Design and implement data infrastructure and pipelines, ensuring reliability and quality. Collaborate with teams for data solutions and optimize processes. Coach junior engineers.

The role involves designing and optimizing data pipelines in Snowflake, developing ETL workflows, collaborating on data integration, ensuring data security, and performance monitoring.

Lead data strategy at Alpha, oversee data functions, build robust data systems, drive product decisions using data insights, and mentor a data team.

Build and maintain automated ETL/ELT data pipelines, improve data quality and monitoring, optimize Postgres and BigQuery schemas and queries, develop internal tooling, support data governance (HIPAA), participate in on-call rotation, and collaborate across engineering teams to scale data systems.

Collect, validate, and maintain market data across asset classes; perform statistical analysis and modeling; ensure data accuracy through QA; troubleshoot discrepancies; produce reports, dashboards, and recommendations; partner with stakeholders to improve data models and analytics practices.