Data Engineer

Health-E Commerce is seeking a Data Engineer to drive the evolution of our modern data platform. As a key member of our centralized Data & Analytics team, you will oversee the design, development, and optimization of data pipelines and infrastructure that power analytics, reporting, and machine learning across the organization.

Reporting directly to the Lead of Data Engineering, you will have a direct impact on day 1 for all of our major data pipelines supporting a broad array of use cases. You’ll collaborate closely with Analytics Engineers, Data Scientists, and cross-functional stakeholders in Marketing, Sales, Finance, and Product to ensure our data systems are scalable, reliable, and aligned with business goals.

• Build and scale our data engineering stack, including ETL/ELT pipelines, transformation workflows, and compute infrastructure across cloud platforms.
• Own the ingestion and integration of new data sources, ensuring they are modeled for downstream analytics, reporting, and machine learning use cases.
• Partner with Analytics and Business teams to define requirements and deliver a robust internal data mart that supports self-service reporting and advanced analytics.
• Collaborate with Data Science to deploy and maintain machine learning models in production, including MLOps, monitoring, and governance.
• Implement and enforce data quality, observability, and governance standards across all pipelines and data assets.
• Drive innovation and efficiency by identifying opportunities to improve data architecture, tooling, and team processes.
• Support strategic initiatives through data-driven insights, ad hoc analysis, and cross-functional collaboration

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
• Minimum 1-4 years of relevant experience in data engineering, software engineering, or analytics
• Strong SQL and Python proficiency 
• Experience working in cloud data platforms (e.g., Azure Synapse, Snowflake, BigQuery, Databricks, Microsoft Fabric). Azure data stack highly preferred. 
• Experience with analytics and BI platforms (PowerBI or similar)
• Strong background in relational databases, ETL tools, scripting languages (Powershell or similar) 
• Proficiency with Git or other collaborative development workflows (e.g., pull requests, code reviews), working in an agile development environment
• Experience with orchestration tools like Apache Airflow, Prefect, or Azure Data Factory for managing complex data workflows preferred
• Demonstrated ability to build processes that support data transformation, structures, accuracy checking, and workload management
• Understanding of statistical data modeling and supporting infrastructure preferred
• Strong communication and stakeholder management skills, with the ability to translate business needs into technical solutions.
• A passion for data, curiosity for solving complex problems, and a drive to create business impact through technology.
• Experience in the e-commerce, marketing or digital health sectors is a big plus

Please use the internal job board in Greenhouse to apply. Applications submitted through this external link will not be tagged as internal.

Health-E Commerce's compensation philosophy is grounded in market data and internal equity to ensure fairness and consistency across the team.  Individuals new to the company should generally expect offers to fall between the entry point and midpoint of the salary range.  Our goal is to provide an offer that supports growth potential within the role and allows for future salary progression.  

• Compensation: $105,000 - 140,000
• Discretionary Annual Bonus Eligibility: Up to 10%
• Medical, Dental, Vision, and 401K with a company match
• Dependent Care, FSA & HSA accounts
• Paid Parental & Bonding Leave
• Flexible PTO & office closure on all major holidays
• Monthly wellness & internet reimbursements
• Professional development including certification support & leadership coaching
• Mental Health resources
• 100% remote within the United States
• Must be able to work EST hours

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