Back
Tier-1 employer, metro location, and a mid-level generalist data engineer profile increase competition.
Core data engineering skills are broadly transferable across industries; life-sciences experience is only a plus.
Explicit 5+ years requirement plus many mandatory AWS/Databricks and data platform skills make filters strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop and maintain ETL/ELT data pipelines for intake into data warehouse and ensure data quality and integrity through validation and testing.
Collaborate with cross-functional data teams to support their data needs and optimize data storage and retrieval for performance and scalability.
Implement and maintain security protocols and partner with teams to drive adoption of data and technology strategies in a fast-paced, Agile/Product environment.
3-5 years of hands-on experience in data engineering or software development with expertise in cloud environments, especially AWS.
Proven experience with AWS services including Glue, Redshift, Athena, CloudFormation, and building real-time data pipelines.
Strong programming skills in Python and knowledge of SQL and database technologies such as MySQL, PostgreSQL, Presto.
Work Experience Required: 3-5 years in relevant data engineering roles; Notice period: Not explicitly mentioned in the JD.
Experience working with cloud data platforms (AWS) and implementing end-to-end data solutions in Agile and product-oriented teams.
Broad knowledge of data lifecycle including data lakes, master data management, data quality, and analytics/AI/ML integrations.
Able to collaborate across global teams, analyze complex environments, and lead process improvements and complex solution implementations.