Data Engineering Lead - Informatica

Role : Data Engineering Lead

Experience : 14+yrs

NOTE : Immediate joiner required or Notice period-serving till Oct 10th, 2025

Skills : ETL, SQL, Oracle, Cloud

ETL / Data Integration Tools : Informatica PowerCenter, Informatica BDM, Informatica IDQ, Informatica Cloud Services, SnapLogic.

Databases : Oracle, Netezza, Snowflake, Azure SQL, Hive.

Data Warehouse & BI : DAC (Data Warehouse Administrative Console), Qlik, OBIEE.

Cloud & Migration : Azure Cloud migration, SaaS-to-Oracle SQL migration.

Programming & Optimization : Advanced SQL, performance tuning, query optimization.

Methodologies : Requirement analysis, test case development, production support, performance tuning, data modelling,and data validation.

Scheduling & Automation : Automic, Query Surge, Jitterbit.

Leadership & Delivery : Offshore/onshore team leadership, L2/L3 support, peer reviews, release management, client communication.

Roles and Responsibilities :

Team Leadership & Management :

- Lead and mentor a team of data engineers across onshore/offshore locations.

- Manage resource allocation, hiring, and onboarding of new team members.

Data Architecture & Strategy :

- Define data engineering best practices, standards, and governance policies.

- Collaborate with enterprise architects and business stakeholders to align data strategies with

business goals.

ETL & Data Integration :

- Oversee development and maintenance of ETL pipelines using tools like Informatica

PowerCenter, BDM, IDQ, and SnapLogic.

- Ensure efficient data ingestion, transformation, and loading processes from various sources

to target systems.

- Optimize ETL workflows for performance and reliability.

Cloud & Migration Projects :

- Lead cloud migration initiatives, especially to Azure, including re-platforming and re-architecting legacy systems.

- Manage SaaS-to-Oracle SQL migration and other data modernization efforts.

Data Warehousing & BI :

- Oversee data warehouse development and maintenance using Snowflake, Netezza, Hive, and

Azure SQL.

- Support BI teams with data modelling and integration for tools like Qlik, OBIEE.

- Ensure high data quality and availability for reporting and analytics.

Performance Tuning & Optimization :

- Conduct advanced SQL tuning and query optimization to improve system performance.

throughput.

Automation & Scheduling :

- Implement and manage job scheduling and automation tools like Automic, Jitterbit, and

Query Surge.