Senior Analytics Engineer

Nest Health

16h•Remote

About The Position

Nest Health is seeking a Senior Analytics Engineer to strengthen its data foundation and build what's next. This role involves owning the end-to-end dbt project, including documentation, testing, dev/prod separation, schema design, and ensuring the transformation layer supports clinical AI. A significant part of the initial work will focus on migrating the platform to AWS. The position also entails owning the semantic layer, defining metrics, establishing data quality standards, and implementing governance processes for self-service analytics. Additionally, the role includes owning data observability by monitoring pipelines, alerting on anomalies, and ensuring data integrity. The orchestration layer will also be managed, involving the evaluation and implementation of a new system to replace ADF as part of the AWS migration. The work will involve a stack including Snowflake, dbt, Python, and a shift to AWS. Clinical data from the EHR, multi-payer claims, care gap data, family-unit models, and an outreach data layer will be utilized. The data platform has direct clinical implications, and the work will support both existing production models and the roadmap for broader clinical AI. Collaboration with clinical, operations, and finance stakeholders on metric definitions and data quality is expected.

Requirements

Strong dbt fundamentals, with a focus on testing, documentation, and downstream consumers.
Snowflake expertise, including schema design, query performance, warehouse cost management, and governance.
AWS orientation, with experience in data engineering work during transitions or a clear path to acquiring it.
Experience with pipeline orchestration tools like Airflow, Prefect, or Dagster.
Python fluency, including the ability to read, write, and debug code comfortably.
Healthcare data literacy, including understanding eligibility files, care gaps, and differences between payer claims and clinical encounter data.
Interest in AI and building trustworthy infrastructure for AI systems.
Strong stakeholder communication skills, with the ability to translate data meanings and build trust.
5+ years owning the transformation layer of a modern data stack.
Production dbt experience.
Strong Snowflake governance.
Python experience (read, write, debug).
Uses AI in day-to-day work and is interested in where it meaningfully changes the system, not just productivity.

Nice To Haves

Prior AWS experience.
Medicaid experience.
Familiarity with CRM & EHR data and workflows.
AWS experience preferred, or strong ability to ramp quickly, especially in a HIPAA-aligned environment.
Experience working with how data supports value-based care operations in Medicaid populations is a plus.

Responsibilities

Own the dbt project end to end, including documentation, testing, dev/prod separation, clean schema design, and making the transformation layer trustworthy enough to support clinical AI.
Migrate the platform to AWS.
Own the semantic layer, including metric definitions, data quality standards, and governance processes.
Own data observability by monitoring pipelines, alerting on anomalies, and building enough coverage to prevent silent failures.
Own the orchestration layer, evaluating options, making decisions, and building out a replacement for ADF as part of the AWS migration.
Work with clinical, operations, and finance stakeholders on metric definitions and data quality.
Support existing production models and the roadmap for broader clinical AI.
Translate data insights for stakeholders and ensure trust in the data.