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Job Description
Structured overview of role & requirementsAbout This Role
Build and maintain scalable data pipelines and architectures including data warehouses and lakes using PySpark and AWS technologies.
Develop and optimize ETL/ELT solutions for large-scale data processing, ensuring data quality, security, and operational effectiveness.
Collaborate with data scientists, architects, and product owners to deliver secure, reliable, and performant data products across the organization.
Minimum Requirements
Work Experience Required: Not explicitly mentioned in the JD.
Strong expertise in PySpark and AWS cloud technologies (e.g., S3, Glue, EMR, Lambda, EC2, DynamoDB).
Experience with modern data platform architectures including Data Lakes, Lakehouse, and scalable ETL/ELT solutions.
Location Requirement: This role is based out of Bengaluru.
Ideal Candidate Profile
Experienced in designing, developing, and maintaining enterprise-scale data pipelines using PySpark and AWS Glue ETL.
Familiarity with Databricks, Snowflake, Airflow, and Git-based source control platforms to accelerate data onboarding and delivery.
Operates effectively in complex, cross-functional environments requiring collaboration with multiple stakeholders including data scientists, architects, and business teams.