Data Engineer

You will work alongside our Staff Data Engineer to keep the analytics and data platform reliable and current. The role is hands-on and defined: you pick up scoped projects and troubleshooting, from fixing a broken ETL job to updating a dashboard, and you carry them with minimal oversight. We move quickly, so the job rewards someone who absorbs context fast, works through problems independently and delivers work that holds. The seat is fully remote on a 2 PM to 11 PM IST schedule, so your day overlaps Pacific time.

What you will do

• Monitor for changes in upstream schemas and update pipelines and transformations as needed.
• Troubleshoot and fix ETL and ELT jobs across Fivetran, Airflow and dbt when data issues occur.
• Improve and debug the SQL behind Superset dashboards and reports.
• Work with engineering and analytics contacts to resolve data quality and access issues.
• Document changes, fixes and improvements so the platform stays legible for the next engineer.
• Find and act on opportunities to improve pipeline performance, reliability, monitoring, observability and automation.

What we are looking for

• 3 to 6 years in data engineering or a closely related role.
• Proficiency in Python and advanced SQL: you can read, debug and optimize code without guidance.
• Hands-on experience with modern ETL and ELT tools such as Fivetran and dbt, and orchestration with Airflow.
• Proficiency with Snowflake or another cloud data warehouse, plus familiarity with BI tools such as Superset, Looker or Tableau.
• AWS experience in a data context, for example Lambda, S3, Glue, EMR, Redshift or Athena.
• The ability to work independently, communicate clearly and deliver assigned work without daily supervision.

Nice to have

• Healthcare data experience such as FHIR or HL7.
• Working knowledge of HIPAA compliance.

What we offer

• A fully remote seat with a fixed 2 PM to 11 PM IST window, matched to Pacific-time collaboration.
• A modern, named stack in daily production use: Fivetran, Airflow, dbt, Snowflake and Superset.
• A Staff Data Engineer to work alongside, with real ownership of what you take on.
• Defined projects and honest scope, so your work ships instead of drifting.

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