Senior Data Engineer- Integration and Analytics

OPEN REQUISITIONS
1. Informatica Developer
Informatica PowerCenter - mapping, workflow development, and debugging
Data pipeline development, transformation logic, and error handling
Collaboration with data architects and business analysts
2. Informatica Developer - PC/SQL/Unix
Informatica PowerCenter with SQL and Unix shell scripting
Database query optimization and source-to-target mapping
Unix/Linux environment - file handling, scheduling, scripting
3. Informatica Administrator
Informatica platform administration - installation, upgrades, patching
Repository management, domain configuration, and performance tuning
User management, licensing, and monitoring of Informatica services
4. Data Integration Engineer - IICS / Talend / Snowflake
IICS (Informatica Intelligent Cloud Services) - cloud-native data integration
Talend - ETL pipeline design, job orchestration
Snowflake - data loading, ELT patterns, performance optimization
UNIX scripting for automation and scheduling
5. Exadata DBA
Oracle Exadata - administration, patching, performance tuning
RAC, ASM, Data Guard - high availability and disaster recovery
Backup and recovery, capacity planning, query optimization
6. BI Reporting Developer
MicroStrategy, Qliksense, Qlikview - dashboard and report development
Power BI and Tableau - self-service analytics and enterprise reporting
SQL - data modeling, query writing, report optimization
Understanding of data warehouse and dimensional modeling concepts

Bachelor's degree in Computer Science, Information Systems, or equivalent
5+ years of hands-on experience in data/analytics domain
Strong SQL skills across all roles
Exposure to cloud data platforms preferred (AWS, Azure, GCP)
Good understanding of data governance and data quality practices

The DNA unit is hiring data professionals specializing in ETL/data integration, database administration, and business intelligence. Candidates should have strong hands-on experience with enterprise data platforms and a solid understanding of data lifecycle management