This is a fully remote position, open to applicants in United States.

📋 Description

• Construct data pipelines, ELT, and infrastructure solutions for both internal data analytics/science and external customer-facing data products.

• Develop automated monitoring, auditing, and alerting mechanisms to guarantee data quality and consistency.

• Collaborate with business and application/solution teams to execute data strategies, establish data flows, and create conceptual, logical, and physical data models.

• Provide reliable data and metrics through AI/LLM tools like Claude, including a governed semantic layer and MCP-based interfaces.

• Enhance data warehouse operations, monitoring, and performance.

• Engage with analysts, developers, business users, and executives.

• Redesign and optimize data processes utilizing AI, including LLM-assisted development, automated documentation, and issue resolution.

• Advocate for Recharge’s values: #day-one, #ownership, #empathy, and #humility.

⛳️ Requirements

• Generally, 5+ years of experience in a data engineering-related position.

• At least 3+ years of practical experience in designing and constructing data pipelines and models for ingesting, transforming, and delivering substantial amounts of data.

• Familiarity with data warehouse, data lake, and enterprise data management platforms, including Snowflake, BigQuery, MySQL, Postgres, RDS, AWS, and GCP.

• Experience in building data pipelines, models, and infrastructure for external, customer-facing analytics applications.

• Strong understanding of data warehousing methodologies such as Kimball and Inmon.

• Proficient in ETL tools including FiveTran, dbt, and Python.

• Experience with workflow orchestration engines like Airflow and Cloud Composer.

• Practical experience with Kubernetes and Docker.

• Advanced proficiency in SQL.

• Strong proficiency in Python.