Senior Data Engineer III

About Stellix

The Stellix Group of companies share a common mission of providing transformative solutions at the intersection of science and technology that enable our customers to deliver a healthier and more sustainable future. Our unique portfolio of companies is focused on helping life sciences and industry manufacturers build, connect, and transform operations and IT to make real progress in breakthrough therapeutics, food, energy, and more.

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 offers a clear path for growth into Principal Data Engineer or Data Architect, based on demonstrated technical expertise, cross-functional impact, and innovation in data engineering. It’s ideal for someone who wants both technical ownership and strategic impact without people management responsibilities.

Responsibilities

Platform & 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.

Technology Best Practices & Innovation (15%)

• Define and implement enterprise scale data engineering best practices, standards and guidelines across the development life cycle.
• Stay up to date on the latest data engineering trends and technologies, advocate for new technologies and champion their adoption to continuously improve our data infrastructure.

Qualifications:

Education: Bachelor’s degree in computer science, data science, software engineering, information systems, or related quantitative field; master’s degree preferred.

Experience: 10+ years of Data Engineering experience, with at least 3 years in modern cloud/data stack. Demonstrated experience designing and implementing enterprise scale data platforms.

Technical Proficiency: Proficient in data management disciplines, including data integration, modeling, building data warehouses/lakes, and data quality, or other areas relevant to data engineering responsibilities and tasks.

Communication & Mindset: Strong communication skills, to be able to clearly articulate technical concepts to non-technical stakeholders. Strong problem-solving skills and a proactive, ownership-driven mindset.

Skills:

• Proficiency in the design and implementation of modern data architectures such as cloud services (AWS, Azure, GCP) and modern data warehouse technologies (Snowflake, Databricks, Redshift, BigQuery). Experience with AWS and Snowflake preferred.
• Experience with ETL/ELT design and development using tools like Informatica, Matillion, AWS Gl