Senior Analytics Engineer

Build canonical data models that create a shared source of truth across the company Define and maintain core business, operational, financial, product, and customer-facing metrics Model data in dbt or equivalent transformation tooling so dashboards, self-serve analytics, and customer reports pull from trusted tables Write tests, documentation, and data quality checks that catch issues before they reach users Create clear definitions for tables, fields, and metrics so teams understand what the data means and when to use it Reconcile metric definitions across internal teams, external reporting needs, and payer customer expectations Trace data lineage and debug dashboards, reports, or tables that change unexpectedly Partner with analysts, data scientists, operations, finance, product, engineering, and customer-facing teams to understand data needs and translate them into reliable models Help build reusable reporting frameworks that make onboarding new payers faster and less manual Partner with the data platform team to evolve warehouse tables, improve data architecture, and strengthen data contracts Improve warehouse cost, performance, and maintainability Support PHI-aware data access patterns and help ensure sensitive healthcare data is modeled and used responsibly Requirements Built analytics engineering, business intelligence, or data modeling systems in a production cloud warehouse environment Written expert-level SQL and designed data models that support reporting, analysis, and decision-making Worked with dbt or an equivalent transformation framework Built tested, documented, reusable data models rather than one-off queries Defined, maintained, or reconciled business-critical metrics across teams Partnered with analysts, data scientists, operators, finance teams, product teams, or customer-facing stakeholders Debugged data quality issues, dashboard changes, metric discrepancies, and lineage problems Worked with cloud data warehouses such as BigQuery, Snowflake, Redshift, Databricks SQL, or similar Balanced speed, correctness, usability, and maintainability when building data assets Communicated clearly with technical and non-technical stakeholders about what data means and how it should be used. Core Competencies Expertise in building and maintaining data models, analytics engineering, and business intelligence systems in cloud environments, with a strong focus on SQL, dbt, and data quality assurance. Ability to collaborate with cross-functional teams to define metrics and ensure responsible use of sensitive data. Highest-signal resume keywords Expert-Level SQL Data Modeling Dbt Transformation Framework Cloud Data Warehousing Data Quality Assurance ATS Optimization Keywords Hard Skills Data Modeling SQL Analytics Engineering Business Intelligence Data Quality Checks Metric Definition Data Lineage Debugging Reporting Frameworks Data Architecture Soft Skills Clear Communication Collaboration Industry Keywords Healthcare Data PHI-Aware Data Access Operational Metrics Customer-Facing Metrics Data Contracts Tools & Technologies Dbt BigQuery Snowflake Redshift Databricks SQL #J-18808-Ljbffr Jobtailor