Analytics Engineer

Role overview Own and improve an analytics platform that supports machine learning, AI work, operational reporting, and product decisions. You will shape data models and warehouse practices, turn complex datasets into reliable dashboards and analysis, and work with product and data science partners to translate business needs into technical solutions.

Responsibilities - Improve data infrastructure, business intelligence processes, and the analytics platform. - Build and maintain dashboards and reports with a business intelligence tool. - Write complex SQL to extract, transform, and analyze data from multiple sources. - Investigate trends, patterns, usage, and root causes, then present findings to stakeholders. - Translate cross-functional requirements into technical specifications and scalable schemas. - Monitor data quality and reporting accuracy, applying sound development practices to data work.

Requirements - At least 3 years of experience in analytics engineering, data engineering, or data analytics, including production pipelines and data models. - Experience building and maintaining data warehouses for analysis and reporting. - Familiarity with orchestration tools, governance, OLAP databases, schema design, and query optimization. - Advanced SQL skills, including work with dbt projects, plus proficiency with Git workflows. - Experience using a major BI tool to create dashboards and reports. - Strong analytical, communication, and presentation skills; familiarity with CI/CD, testing, documentation, and modular coding.

Nice to have - Experience with healthcare data or in the health sector. - Python or R experience beyond SQL or SAS, and deeper experience with dbt.

Benefits and work setup - Opportunity to shape early technical and product foundations, work with substantial ownership, and build production systems used in healthcare operations.