Mphasis
Website:
mphasis.com
Job details:
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.
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