Data Integration Engineer

About the Team:

The Data Integration Engineer reports to the Data Management & Analytics organization within the Information Systems/Enterprise IT & Strategy. In this role, you will be responsible for designing, developing, and maintaining robust data integration solutions. Your primary focus will be building ETL pipelines using Informatica Intelligent Cloud Services (IICS/IDMC) to support our data warehousing and analytics initiatives.The ideal candidate has a strong background in Computer Science/any engineering , deep expertise in SQL and RDBMS, and a solid understanding of Data Warehousing principles.

Key Responsibilities

• ETL Development: Design, develop, test, and deploy complex ETL/ELT processes using Informatica Cloud (IICS) to move data between diverse sources and targets.
• Database Engineering: Write high-performance SQL queries, stored procedures, and views. Analyze and optimize query performance within Relational Database Management Systems.
• Data Warehousing: Collaborate on data modeling (Medallion architecture) and implement data warehousing strategies to support business intelligence reporting.
• Data Quality & Maintenance: Monitor daily data loads, troubleshoot production issues, and ensure data integrity and accuracy across systems.
• Collaboration: Work closely with business analysts, data scientists, and stakeholders to understand data requirements and translate them into technical specifications.

Documentation: Maintain detailed technical documentation regarding data mappings, data dictionaries, and ETL process flows

• Education: Bachelor’s degree in computer science, Engineering, Information Systems, or a related technical field.
• Experience: Minimum of 3 years of hands-on experience in data integration and ETL development.
• Informatica Expertise: Proven experience working with Informatica Cloud (IICS) (Data Integration, Application Integration).
• Strong SQL Skills: Expert-level proficiency in SQL (joins, subqueries, window functions, indexing) and experience working with traditional RDBMS (e.g., Oracle, SQL Server, PostgreSQL, or MySQL).

• Data Warehousing: Solid understanding of Data Warehousing concepts, including dimensional modeling, CDC (Change Data Capture), and SCD (Slowly Changing Dimensions).