Data Engineer

Location: Bangalore
Job Summary:
We are seeking an experienced Data Engineer with deep expertise in AWS-based data ecosystems and hands-on experience with relational databases such as Aurora or Oracle. The ideal candidate will possess strong knowledge of data processing, ETL/ELT pipelines, and cloud-native engineering practices. Experience with Snowflake, Databricks, or large-scale data migrations is highly desirable. Prior exposure to the banking or financial services sector is a significant advantage.
Responsibilities:
Design ETL/ELT pipelines using AWS services including S3, Glue, EMR, Lambda, and Step Functions.
Build and maintain data ingestion frameworks leveraging AWS Aurora (MySQL/Postgres) and Oracle.
Develop and optimize SQL for large-scale, high-volume datasets.
Collaborate with cross-functional teams including analysts, data scientists, and business stakeholders.
Implement data quality and validation frameworks with automated monitoring and ing.
Support cloud data platform migrations including AWS Aurora to Snowflake migration (schema conversion, data movement, performance validation).
Integrate with Snowflake, Databricks, or other modern data platforms.
Troubleshoot performance issues across pipelines, compute layers, and storage systems.
Mandatory Skills:
AWS expertise across S3, Glue, EMR, Lambda, CloudWatch, IAM, and Step Functions.
Hands-on experience with Aurora or Oracle for ingestion, transformation, and performance tuning.
Advanced SQL proficiency including query optimization, stored procedures, and execution plan analysis.
Strong understanding of data modeling, ETL/ELT concepts, and data warehousing architectures.
Python or PySpark development for data processing and automation.
Experience with Snowflake migrations, especially Aurora to Snowflake schema conversion, data replication, and performance tuning.