Database Performance Engineer

Strong expertise in enterprise database performance tuning across mainframe and cloud environments. The ideal candidate will have deep knowledge of SQL optimization, workload management, concurrency handling, and high-throughput system stabilization.

• Perform database engineering and performance tuning across large-scale enterprise systems.

• Optimize SQL queries and analyze execution plans using tools such as:

  • EXPLAIN

  • Query Store

  • AWR / ASH

  • DB2 Visual Explain

• Work with mainframe data technologies including:

  • DB2 for z/OS

  • IMS DB

  • VSAM

  • Knowledge of JCL/COBOL for understanding data-access patterns (preferred)

• Manage and tune AWS database services including:

  • AWS RDS (MySQL, Postgre
    
    SQL, SQL Server, Oracle)

  • Redshift

  • Athena

  • Glue

  • S3

• Configure and optimize:

  • Workload Management (WLM)

  • Distribution and sort keys

  • Partitioning strategies

  • Compression techniques

• Improve high-throughput workloads (>1000 TPS), reduce query latency, and stabilize peak-hour performance.

• Design and manage:

  • Indexing strategies

  • Statistics collection

  • Partitioning models

  • Locking and concurrency control (deadlocks, isolation levels)

• Apply data modeling best practices, including:

  • OLTP vs. OLAP design considerations

  • Normalization and denormalization trade-offs

• Utilize Linux and mainframe utilities for performance diagnostics.

• Develop automation scripts using Python or Shell scripting.

• Collaborate with stakeholders and communicate performance insights effectively.

• Data Concepts & Data Modelling

• Python for Data Science

• MySQL

• Statistics & Analytics

• SQL Performance Tuning

• AWS Data Services (RDS, Redshift, Athena, Glue, S3)

• Mainframe Database Technologies (DB2 z/OS, IMS, VSAM)

6–8 Years