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Mid-level metro Data Engineer role with common AWS/Snowflake/PySpark skills attracts many qualified applicants.
Core cloud and data engineering skills are highly transferable across industries despite retail preference.
Mandatory 3+ years plus specific AWS, PySpark, Snowflake and Glue experience increases screening but not extremely rigid.
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Design, develop, maintain, and support business intelligence backend systems including data warehouses and data lakes using AWS, PySpark, and Snowflake.
Build and enhance ETL frameworks and data pipelines leveraging AWS services like Lambda, Glue, SNS, SQS, and Step Functions to support data integration and transformation.
Collaborate with business and platform teams to align data solutions with requirements, propose best practices, perform troubleshooting, and ensure scalability and cost optimization.
Minimum 3+ years of experience in application design, development, and analysis with expertise in AWS cloud technology stack and Snowflake.
Bachelor's or Master's degree in Computer Science or equivalent experience.
Experience with AWS services (Lambda, Glue, PySpark, SNS, SQS, Step Functions), GCP, and implementing data transformations for data warehouse and lakes.
Location Hyderabad (Hybrid); Notice period consideration up to 20 days.
Hands-on expertise in AWS cloud solutions and PySpark for building and optimizing ETL frameworks and data pipelines at scale.
Experience working closely with business stakeholders for data integration, governance, and alignment with corporate technology strategies.
Capable of independent decision-making, proactive problem-solving, and identifying cost optimization in complex data engineering environments.