Data Engineer

About the role

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.

Responsibilities

• 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

Requirements

• 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

Qualifications

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

Pay

Compensation: $105,000 - 140,000

Schedule

Must be able to work EST hours