Analytics Engineer, Data Platform

The Analytics Engineer, Data Platform at AndHealth designs and maintains dbt models and ETL pipelines, and develops the semantic layer for self-service analytics across clinical, pharmacy, billing, and care operations.

Responsibilities

• Create, implement, and maintain dbt models to transform raw data from clinical, pharmacy, billing, and care operations into clean, domain-specific data marts.
• Collaborate with Data and Software Engineering on ETL/ELT pipeline design, data ingestion, and raw-to-staging transformations to ensure data is delivered in a usable form for 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 such as lineage documentation, cataloging, access control, and column-level documentation in dbt.
• Become a domain expert in the assigned area (pharmacy operations, billing, or care operations) by thoroughly understanding business logic and translating it into accurate, scalable data models.
• Collaborate with analysts to understand data needs, accelerate workflows, and reduce time spent on ad hoc data prep, enabling focus on higher-order analysis and strategy.
• Contribute to platform level decisions including warehouse organization, modeling conventions, CI/CD for dbt, 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

• Strong SQL proficiency with the ability to write complex queries, CTEs, window functions, and performance-optimized transformations across large datasets.
• Hands-on experience with dbt (Core or Cloud): understanding of the modeling layer, ref() dependencies, tests, macros, and structuring a well-organized dbt project.
• Solid understanding of data warehouse concepts, including dimensional modeling, mart layers, slowly changing dimensions, and staging/intermediate/mart separation.
• Experience with ETL/ELT pipelines and partnering with data or software engineers on data ingestion.
• Comfort with the command line, including running scripts, managing files, and troubleshooting basic shell operations.
• Strong analytical instincts: ability to interrogate data, identify anomalies, trace root causes, and communicate findings to technical and non-technical audiences.
• Ability to operate in ambiguous, fast-moving environments with competing priorities.
• Bachelor's degree in Computer Science, Economics, Engineering, Mathematics, or a related quantitative field, or equivalent.

Technologies

• SQL
• dbt
• Omni
• Looker
• Metabase
• Python

Benefits

• Equal investment and support for our people and patients
• A fun and ambitious start-up environment with a culture that takes on big things, takes risks, and learns quickly
• Opportunities to demonstrate creativity, innovation, and conscientiousness, and to collaborate effectively
• A team of highly skilled, welcoming, and supportive colleagues with diverse strengths
• Commitment to ongoing learning and growth, both personally and professionally
• Full-time employees are eligible for a benefits package including Medical, Dental, and Vision Insurance, Paid time off, Short- and Long-Term Disability, and more