Description

What You'll Do:

• Design, develop, and maintain complex SQL queries, stored procedures, functions, and views for enterprise applications.
• Build and manage ETL/ELT pipelines using tools like Informatica, SSIS, DataStage, or Azure Data Factory for structured and semi-structured data.
• Perform data extraction, transformation, and loading from multiple legacy systems (mainframe, flat files, ERP/CRM systems) into modern data platforms.
• Develop and optimize data models (OLTP/OLAP), ensuring efficient query performance and scalability.
• Implement incremental data loads, CDC (Change Data Capture), and batch processing frameworks.
• Work on legacy system modernization, migration, and integration into cloud or modern data platforms.
• Design and implement data validation, reconciliation, and quality frameworks across pipelines.
• Ensure data governance, audit logging, traceability, and compliance for enterprise data workflows.
• Collaborate with reporting/BI teams to enable data availability for dashboards and analytics.
• Optimize SQL performance using indexing, partitioning, query tuning, and execution plan analysis.
• Prepare technical documentation, data flow diagrams, and integration design specifications.
• Participate in architecture discussions, system upgrades, and performance tuning initiatives.

Expertise You'll Bring:

• 5 to 8 years of experience in SQL development, data engineering, or data integration roles.
• Strong expertise in SQL (Oracle / SQL Server / PostgreSQL / MySQL) with hands-on experience in writing complex queries, stored procedures, and performance tuning.
• Experience working with ETL tools like Informatica, SSIS, DataStage, or similar data integration platforms.
• Solid understanding of data warehousing concepts, dimensional modelling (star/snowflake schema), and data transformation techniques.
• Hands-on experience in data migration and legacy system integration.
• Knowledge of data quality checks, validation, and reconciliation processes.
• Familiarity with batch processing, scheduling tools (SQL Agent, Control-M, Airflow).
• Experience in handling structured and unstructured data from multiple sources including flat files, APIs, and databases.
• Exposure to cloud platforms (Azure/AWS) for data integration is an added advantage.
• Strong analytical, debugging, and problem-solving skills.
• Excellent communication and stakeholder management capabilities

Key Skills

Education

Any Graduate