Data Engineer

FSAStore.com

2h•$105,000 - $140,000•Remote

About The Position

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.

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
Demonstrated ability to build processes that support data transformation, structures, accuracy checking, and workload management
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.

Nice To Haves

Experience with orchestration tools like Apache Airflow, Prefect, or Azure Data Factory for managing complex data workflows preferred
Understanding of statistical data modeling and supporting infrastructure preferred
Experience in the e-commerce, marketing or digital health sectors is a big plus

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