Senior Data Engineer - Remote Data Platform & Pipelines

Lyric; Providence (RI); Remote; USD 125,000 - 188,000; Full time

Job summary

Lyric is seeking a Senior Data Engineer to build the data foundation for its healthcare decision intelligence platform. You’ll own end-to-end data pipelines, implement the canonical data model in production, and ensure data quality and observability across a multi-tenant environment.

You’ll work with a team led by a Principal Data Engineer, be hands-on with Snowflake, Airflow, dbt, and Python, and help shape the architectural direction while mentoring others.

Qualifications

• Bachelor's degree in software engineering, computer science, or a related field.
• 5+ years building and owning production data pipelines.
• Strong Snowflake experience (streams/tasks, clustering, RBAC).
• Production experience with dbt and Airflow; solid modeling/structuring of DAGs.
• Strong Python and SQL proficiency; data modeling for multi-consumer schemas.

Responsibilities

• Design, build, and own data pipelines using Airflow, dbt, and Snowflake.
• Implement canonical data model in production and contribute to architecture direction.
• Add automated validation and data quality checks in pipelines.
• Instrument pipelines for observability: freshness, lineage, and failure alerts.
• Collaborate with consumer teams across invoicing, analytics and reporting.
• Migrate existing workloads to the unified framework without disruption.
• Participate in on-call rotation for data incidents and post-incident reviews.
• Uphold version control, testing, CI/CD, and documentation standards.
• Mentor engineers and raise the technical level of the team.

Skills

Python

SQL

Snowflake

dbt

Airflow

Data modeling

Data pipelines

CI/CD

Testing

Observability

Education

Bachelor's degree in Software Engineering, Computer Science, or a related field

Tools

Snowflake

dbt

Airflow

Job description

Lyric is seeking a Senior Data Engineer to build the data foundation for its healthcare decision intelligence platform. You’ll own end-to-end data pipelines, implement the canonical data model in production, and ensure data quality and observability across a multi-tenant environment.

You’ll work with a team led by a Principal Data Engineer, be hands-on with Snowflake, Airflow, dbt, and Python, and help shape the architectural direction while mentoring others.