Senior Data Engineer

Summary

Join Virta Health, a company revolutionizing type 2 diabetes and weight-loss care, as a Senior Data Engineer, Analytics. You will play a crucial role in building and scaling the data foundation, architecting data models, optimizing pipelines, and creating self-service analytics tools. This position requires strong experience in data engineering, proficiency in SQL and Python, and expertise with cloud data warehouses and analytics tools. You will collaborate with various teams to ensure data quality, integrity, and accessibility. The role offers the opportunity to design scalable solutions and make a significant impact on the company's growth. Virta Health is a remote-first company with a competitive compensation package.

Requirements

• 5 - 8 years of experience in data engineering, analytics engineering, or a related field
• Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, or a related field, with strong coursework in databases, data structures, and system design, or equivalent industry experience
• Strong proficiency in SQL and Python and experience working with cloud data warehouses (e.g., BigQuery), model analytics pipeline and orchestration tools (e.g., dbt, Dagster, Airflow), and self-service analytics tools (e.g., Looker)
• A solid understanding of analytics database concepts, ELT pipelines, and best practices in data modeling
• Ability to work cross-functionally with stakeholders to gather requirements and deliver impactful solutions
• Strong problem-solving skills and a passion for building scalable data solutions

Responsibilities

• Design, develop, and maintain ELT data pipelines to ensure reliable and efficient data processing
• Build and optimize data models to support analytics and reporting needs
• Collaborate with analysts and business stakeholders to create and maintain self-service analytics tools that provide meaningful insights
• Ensure data quality and integrity through testing, validation, and documentation
• Monitor and improve analytics database performance, optimizing queries and warehouse costs
• Automate and improve our data pipeline workflows for scalability and efficiency
• Work closely with product, engineering, and business teams to understand data requirements and translate them into effective solutions
• Get Fully Onboarded & Understand the Data Ecosystem – Gain deep familiarity with our data warehouse, ELT pipelines, and BI setup. Meet with key stakeholders (engineering, analytics, and business teams) to understand existing data pain points, priorities, and opportunities for improvement
• Lead the migration of our Legacy Looker instance to Google Looker (core) - Our Looker instance has been around since before Google acquired Looker, so we’re due for an upgrade! Help create the plan for transitioning work into new Looker, including establishing best practices. Serve as the team’s technical expert as we begin to build a better BI experience for everyone
• Audit & Document the Current Data Stack – Conduct a review of data pipelines, transformation logic, and data models, identifying inefficiencies, inconsistencies, or areas for optimization. Create documentation to clarify how data flows through the system
• Tackle a Quick Win to Improve Data Reliability or Performance – Identify and execute one or two high-impact optimizations, such as fixing a slow-running query, improving a model, or cleaning up a problematic dashboard, to build credibility and show immediate value
• Establish Best Practices & Start Automating Key Workflows – Introduce small but meaningful improvements to pipeline reliability, automated testing, and version control processes to ensure data consistency and governance
• Align on Strategy & Roadmap for Future Improvements – Work with stakeholders and the analytics team to define priorities for the next 6-12 months, ensuring alignment with business needs. Develop an initial roadmap for architecture, scalability, and self-serve analytics improvements

Preferred Qualifications

Experience in the healthcare industry or otherwise handling sensitive data

Benefits

• Compensation range is $167,249 - $216,000
• Remote work