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Job Description
Structured overview of role & requirementsAbout This Role
Develop and maintain ETL/ELT pipelines for data ingestion into the data warehouse with end-to-end ownership.
Optimize data storage and retrieval for performance and scalability, ensuring data quality, integrity, and security.
Collaborate with cross-functional teams including data architects, analysts, scientists, and Enterprise Data Platform teams to support data and technology strategy adoption.
Minimum Requirements
3-5 years hands-on experience implementing and operating data capabilities and solutions, preferably in cloud environments.
Expertise in Databricks, AWS data engineering services (Glue, Lambda, S3, Redshift, Athena, Lake Formation), CloudFormation, GitHub workflows, and API building on AWS.
Strong programming skills in Python, PySpark and experience with SQL and databases such as MySQL, PostgreSQL, Presto.
Work Experience Required: 5+ years in data engineering or software development. Functional domain experience in Life Sciences R&D is a plus but not mandatory.
Ideal Candidate Profile
Experienced in design and implementation of real-time data ingestion pipelines on AWS with strong cloud data platform knowledge.
Demonstrated ability to lead process improvements and deliver complex data solutions in agile/product-based environments, collaborating globally.
Familiarity with full data management lifecycle including data lakehouses, data quality, master/reference data management, and analytics/AI/ML technologies.