Senior Data Engineer – AWS

About the Role

We are looking for a Senior Data Engineer to support and enhance our config-driven, multi-tenant AWS Data Lakehouse platform. You will work across multiple tenants, contribute to framework development, resolve production issues, and provide technical consulting to onboarding teams. This is a hands-on engineering role requiring strong AWS, Python, PySpark, SQL, and Terraform skills within a fast-paced, infrastructure-as-code heavy environment.

Required Skills & Experience

• 7+ years of hands-on data engineering experience in cloud-native environments (AWS required)
• 5+ years of strong proficiency in Python and PySpark for data processing, transformation, and pipeline development
• 7+ years of experience in advanced SQL skills , complex queries, window functions, performance tuning, query optimization across Redshift and Spark SQL
• 5+ years of hands on experience with AWS Glue, EMR, Databricks, or similar Spark-based compute services
• 5+ years of experience with Terraform for infrastructure provisioning and management
• 5+ years of experience in different ingestion & ETL tools like Glue, DMS, Golden Gate, HVR, Informatica, Talend etc.
• Experience supporting multi-tenant platforms, understanding tenant isolation, shared frameworks, and config-driven patterns
• Strong troubleshooting and debugging skills — ability to diagnose and resolve production pipeline failures quickly
• Excellent communication skills, ability to engage with multiple tenant teams, provide technical consulting, and explain complex solutions clearly

Preferred Qualifications:

• Experience with Airflow or Autosys for workflow orchestration
• Experience with AWS Lake Formation for governance and fine-grained access control
• Familiarity with SAP source systems or enterprise ERP data
• Experience with CloudWatch for monitoring and observability
• AWS GovCloud experience
• Data modeling experience (star schema, data vault)
• Experience with Parquet, Avro, and Iceberg file/table formats