Senior Data Engineer

About Stellix

Stellix helps organizations in the life sciences and other critical industries connect strategy, systems, and teams so they can turn digital and AI investments into measurable operational results. Join our team as we design, implement, and govern the adaptive operating models that produce outcomes that matter to our clients and the communities they serve.

The Position

We are seeking a Senior Data Engineer to join our growing Enterprise Data & Analytics team. Our mission is to empower every team across the organization with timely, trusted, and actionable data. In this role, you will own and build our Enterprise Data Platform (EDP), which supports analytics and insights across the organization. Our technology stack includes Snowflake, dbt, Fivetran, Airflow, and Power BI, all running in the AWS cloud.

This is an individual contributor role with a strong emphasis on technical leadership, including ownership of architectural decisions and driving best practices, but without direct people management responsibilities. You’ll be responsible for designing, developing, and maintaining all components of the EDP. You will transform raw data into reliable, actionable insights that empower strategic decision-making enterprise wide.

This role is ideal for someone who wants both technical ownership and strategic impact without people management responsibilities.

ResponsibilitiesPlatform & Architecture (25%)

• Responsible for scoping, architecting, designing, and developing robust data engineering solutions—including data pipelines, data integration, and infrastructure.

• Support the data architect in the creation of conceptual and logical data models. Own the creation of physical data model optimized for analytics, reporting, and AI/machine learning use cases.

• Serve as the technical owner of the data platform—making architectural decisions, maintaining high code quality, and delivering scalable, reliable solutions.

Pipeline Development & Data Integration (50%)

• Integrate data from diverse sources, including databases, APIs, flat files and cloud platforms.

• Design, and build performant, scalable data pipelines using tools like dbt, Fivetran, and Airflow.

• Troubleshoot issues with production data pipelines and implement monitoring and alerting as needed.

• Design and deliver curated datasets to support analytics engineers in building AI and BI solutions.

Collaboration & Data Quality (10%)

• Collaborate across business, governance, QA, and analytics teams to ensure data quality, consistency, and successful solution delivery.

• Implement data quality frameworks and automated tests to ensure integrity, trust, and traceability across the pipeline.