Senior Data Engineer

Recharge is the subscription platform for the world’s fastest-growing and most innovative brands. Shopify’s premier subscription solution, Recharge is on a mission to build the future of commerce around customer retention.

Known for its relentless product innovation and focus on ease of use, Recharge helps merchants deliver seamless customer experiences that drive customer retention and revenue growth. The Recharge platform leverages data from over 100 million shoppers to help brands more successfully set up, manage, and grow their subscription businesses.

Recharge is a hands-on partner to over 20,000 brands globally — including quip, Dr. Squatch, Blueland, Estrid, Oats Overnight, Bobbie, and more.

Learn more at: getrecharge.com

The centralized Data and Analytics team at Recharge delivers critical analytic capabilities and insights for Recharge’s business and customers.

As a Senior Data Engineer, you will build scalable data models and infrastructure that power internal business analytics and customer-facing data products. Your work will empower data analysts to derive deeper strategic insights from our data, and will build end-to-end interfaces and integrations that surface data and metric insights directly to our merchants.

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  Build data pipeline, ELT and infrastructure solutions to power internal data analytics/science and external, customer-facing data products.

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  Create automated monitoring, auditing and alerting processes that ensure data quality and consistency.

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  Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models

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  Build next-generation analytics by delivering trusted data and metrics via AI/LLM tools (e.g., Claude), including a governed semantic layer and MCP-based interfaces for internal and external users.

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  Seek ways to continually improve the operations, monitoring and performance of the data warehouse

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  Influence and communicate with all levels of stakeholders including analysts, developers, business users, and executives.

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  Redesign and optimize existing data processes using AI (e.g., LLM-assisted development, automated documentation, issue resolution) to improve team productivity and enhance data quality across the data warehouse

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  Live by and champion our values: #day-one, #ownership, #empathy, #humility.

• Typically, 5+ years experience in a data engineering related role (Data Engineer, Data Platform Engineer, Analytics Engineer etc) with a track record of building scalable data pipeline, transformation, and platform solutions.

• 3+ years of hands-on experience designing and building data pipelines and models to ingesting, transforming and delivery of large amounts of data, from multiple sources into a Dimensional (Star Schema) Data Warehouse, Data Lake.

• Experience with a variety of data warehouse, data lake and enterprise data management platforms (Snowflake, BigQuery, MySQL, Postgres, RDS, AWS, GCP)

• Experience building data pipelines, models and infrastructure powering external, customer-facing (in addition to internal business facing) analytics applications.

• Solid grasp to data warehousing methodologies like Kimball and Inmon

• Experience working with a variety of ETL tools. (FiveTran, dbt, Python etc)

• Experience with workflow orchestration management engines such as Airflow & Cloud Composer

• Hands on experience with Data Infra tools like Kubernetes, Docker

• Expert proficiency in SQL

• Strong Python proficiency