Remote Senior Data Platform Engineer - Healthcare

Lyric

Richmond (VA)

Remote

USD 125,000 - 188,000

Full time

6 days ago
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Job summary

Lyric is seeking a Senior Data Engineer to build the data foundation for its healthcare decision intelligence platform. You will design and deliver production data pipelines using Airflow, dbt, and Snowflake, implement the canonical data model, and ensure data quality with automated checks and observability.

You will work closely with the Principal Data Engineer to contribute to architectural direction and platform improvements.

Qualifications

  • Bachelor's degree in software engineering or computer science.
  • 5+ years of experience in data engineering, building and owning production data pipelines.
  • Strong Snowflake experience with streams and tasks, RBAC, clustering, and micro-partitions.
  • Production experience with dbt and Airflow including model/DAG structuring.
  • Strong programming in Python and SQL.

Responsibilities

  • Design, build, and own data pipelines in a unified framework.
  • Implement the canonical data model in production and contribute to architecture.
  • Build automated validation and data quality checks into pipelines.
  • Instrument pipelines for observability (freshness, lineage, alerts).
  • Contribute to self-service data delivery for consuming teams.
  • Collaborate with cross-functional teams (invoicing, analytics, reporting).
  • Migrate workloads to the unified framework without disrupting consumers.
  • Participate in on-call rotation and incident reviews.
  • Maintain high engineering standards (version control, testing, CI/CD, docs).
  • Mentor engineers and raise the technical level of the team.

Skills

Python
SQL
Data modeling
Airflow
dbt
Snowflake
CI/CD
Communication

Education

Bachelor's degree in software engineering or CS

Tools

Airflow
dbt
Snowflake
Datadog

Job description

Lyric is seeking a Senior Data Engineer to build the data foundation for its healthcare decision intelligence platform. You will design and deliver production data pipelines using Airflow, dbt, and Snowflake, implement the canonical data model, and ensure data quality with automated checks and observability.

You will work closely with the Principal Data Engineer to contribute to architectural direction and platform improvements.

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