AndHealth is seeking an Analytics Engineer to design and maintain dbt models and ETL pipelines, and to build the semantic layer that powers self-service analytics across clinical, pharmacy, billing, and care operations. This onsite role in Columbus, Ohio focuses on turning raw data into trusted, domain-specific data products for analysts and stakeholders.
The position emphasizes collaboration with Data and Software Engineering, ownership of the semantic layer in Omni, governance, and close partnership with analysts to streamline data workflows and enable faster, more reliable analytics.
Responsibilities
- Design, build, and maintain dbt models that transform raw clinical, pharmacy, billing, and care operations data into clean, domain-specific data marts.
- Partner with Data and Software Engineering on ETL pipeline design, data ingestion, and raw-to-staging transformations to ensure data arrives in a form usable by analytics engineers.
- Develop and own the semantic layer in Omni by defining governed metric definitions, curated datasets, and self-service data products that analysts and stakeholders can consume directly.
- Build a comprehensive testing suite across the data platform, including schema tests, data quality checks, anomaly detection, and SLA monitoring to foster trust in the data.
- Implement and maintain data governance practices including lineage documentation, cataloging, access control, and column-level documentation in dbt.
- Become a domain expert in pharmacy operations, billing, or care operations by translating business logic into accurate, scalable data models.
- Collaborate with analysts to understand data needs, accelerate workflows, and reduce time spent on ad hoc data preparation.
- Contribute to platform-level decisions around warehouse organization, modeling conventions, dbt CI/CD, and tooling standards across the Analytics Engineering team.
- Proactively identify data quality issues, gaps in coverage, and opportunities to improve the reliability and usability of the data platform.
Requirements
- Education: Bachelor's degree in Computer Science, Economics, Engineering, Mathematics, or a related quantitative field, or equivalent.
- Strong SQL proficiency, capable of writing complex queries, CTEs, window functions, and performance-optimized transformations across large datasets.
- Hands-on experience with dbt (Core or Cloud): understanding the modeling layer, ref() dependencies, tests, macros, and how to structure a well-organized dbt project.
- Solid understanding of data warehouse concepts: dimensional modeling, data marts, slowly changing dimensions, and the staging/intermediate/mart separation.
- Experience working with ETL/ELT pipelines and partnering with data or software engineers on data ingestion.
- Comfort with the command line: run scripts, manage files, and troubleshoot basic shell operations.
- Strong analytical instincts: able to interrogate data, identify anomalies, trace root causes, and communicate findings clearly to both technical and non-technical audiences.
- Ability to thrive in ambiguous, fast-moving environments with competing priorities.
Technologies
- SQL
- dbt
- Omni
- Looker
- Metabase
- Python
Benefits
We support equal investment and care for our people and patients, within a startup culture that embraces ambitious goals, calculated risk-taking, and rapid learning. The team values creativity, collaboration, and conscientious work, and welcomes diverse, kind colleagues who contribute unique strengths. We provide ongoing opportunities for growth, both personally and professionally, and full-time employees are eligible for benefits including medical, dental, and vision insurance, company-paid time off, short- and long-term disability, and more.
