Description

Design and maintain data pipeline architectures for large-scale processing and business intelligence. Own the full lifecycle of ETL/ELT systems, from extraction to loading across diverse sources.

Responsibilities

• Build and optimize ETL/ELT architectures to assemble complex datasets meeting functional requirements.
• Automate manual processes and redesign infrastructure to improve scalability and data delivery efficiency.
• Develop analytics tools to provide actionable insights into customer acquisition and operational metrics.
• Collaborate with Data Scientists and Product Managers to implement technical solutions and meet sprint milestones.

Required Skills

• 5+ years of hands-on experience building ETL/ELT data pipelines on cloud platforms (GCP preferred; AWS or Azure acceptable).
• 5+ years of experience building and operationalizing data processing systems.
• Strong Python scripting experience.
• 2+ years of experience with NoSQL databases.
• 2+ years of experience with data platforms including Data Warehouses, Data Lakes, and ODS.
• 2+ years of experience automating CI/CD pipelines using tools like Jenkins, GIT, or Control-M.
• Proficiency in Python/R, Scala, Java, Hive, Spark, or Kafka.
• Working experience with clinical data.

Preferred Skills

• 3+ years of experience working with healthcare or clinical data.
• Experience with GCP Dataflow, Dataproc, Functions, Whistle map SDK, or Google Healthcare API/FHIR store.
• Data analysis and data mapping skills.

Key Skills

Education

Any Graduate