Senior Data Engineer

Interra Health•Boston, MA

16h•Remote

About The Position

Interra Health is a fast-growing healthcare technology company transforming how providers and patients navigate the prescription journey. Formed through the merger of DoseSpot, Arrive Health, and pVerify, Interra Health delivers trusted eligibility, real-time coverage and pricing insights, prescribing tools, and pharmacy transparency at the point of care—helping providers make informed decisions and patients access the right medications with greater clarity and affordability. Backed by strong market momentum and a bold vision for the future of connected care, Interra Health offers the chance to join an innovative, mission-driven team working at the intersection of software and healthcare to reduce friction, improve access, and make the healthcare experience better for everyone. The Role: We are seeking a highly skilled and experienced Senior Data Engineer to collaborate with us to design, implement, and manage our organization’s data platform. The ideal candidate will possess deep expertise in data modeling, database design, cloud data platforms, data governance practices, and data integration tools. This role requires a hands-on technical team member who thrives in a player-coach capacity—someone who can both collaborate on architectural solutions and actively contribute to their development. As a Senior Data Engineer , you will work closely with cross-functional teams to ensure our data systems are scalable, secure, accessible, and aligned with strategic business goals. You will also be expected to engage with global teams, including offshore engineering resources, to drive consistent implementation standards and foster a culture of knowledge sharing and continuous improvement.

Requirements

4+ years of experience in data engineering.
Proven expertise in AWS, Azure, Snowflake, dbt, and Python.
Strong background in data warehouse architecture, data modeling, and performance tuning.
Proficiency in SQL, dbt, and Python for data transformation and orchestration.
Experience with cloud-native architecture, DevOps practices, and CI/CD pipelines in Azure, AWS, and GitHub.
Excellent communication and collaboration skills with the ability to influence technical direction and strategy.
Fully proficient in data engineering; applies a complete understanding of the discipline’s principles, tools, and company practices to deliver work.
Owns assigned projects end to end and produces results with minimal oversight.
Works on problems of diverse scope where analysis requires identifying and evaluating factors from limited information.
Devises solutions by adapting and applying existing approaches, exercising judgment within established practices.
Impact is primarily at the team and project level.
Builds productive working relationships and influences senior partners outside own immediate team on technical matters.
Adapts communication style for diverse audiences to explain approaches and gain support for recommendations.

Responsibilities

Design and implement scalable, secure, and high-performance data solutions across a multi-cloud organization that includes AWS and Azure.
Define and enforce data engineering standards, best practices, and architectural patterns.
Collaborate with a highly motivated team to evaluate and integrate emerging technologies that enhance the data platform’s capabilities.
Drive platform evolution by identifying opportunities for AI-powered automation and implementing solutions that enhance data workflows.
Develop ELT pipelines using AWS Infrastructure, Azure Infrastructure, Apache Airflow, Snowflake, and dbt.
Oversee the design, development, and optimization of a unified data platform across cloud environments.
Manage the development and maintenance of data models and schema designs to support efficient data storage and retrieval.
Manage schema evolution processes from product data sources to Snowflake.
Optimize data processing workflows for performance, scalability, and reliability.
Act as a subject matter expert for internal stakeholders and clients, addressing technical inquiries and providing strategic guidance.
Implement and maintain robust data governance, security, and compliance frameworks.
Ensure data quality, security, and integrity through effective validation, cleansing, testing, and monitoring techniques.