Senior Data Engineer

Key Responsibilities:

• Develop ETL/ELT jobs to ingest, transform, and load data from multiple source systems into Data Warehouse / Data Lake platforms based on the approved analysis and design documents.
• Hands-on experience in building and maintaining ETL/ELT pipelines, especially using Oracle Data Integrator (ODI) or Airflow. Troubleshoot and optimize data pipelines to improve scalability, performance, and operational efficiency.
• Utilize jobs, workflows, APIs and streaming to manage large-scale data processing workloads.
• Support ML/AI initiatives through data preparation, exploratory analysis, and metric definition.
• Design and optimize data models, data marts, and data warehouse structures to support analytics and reporting.
• Ensure data quality, governance, reliability, and performance across enterprise data platforms.
• Mentor a team of engineers while driving best practices in data modeling and system design for data-heavy applications.

Experience:

• Bachelor's degree in Computer Science, Information Technology, Data Engineering, or related fields.
• Minimum 3+ years in data engineering across large/complex datasets and operate pipelines at scale and integrating multiple source systems.
• Solid background in Data engineering best practices.
• Strong skills in dbt, Python, PySpark, Spark streaming and Advanced SQL.
• Understanding and hands-on exposure to DataOps practices, including CI/CD for data pipelines, monitoring, logging, and data quality automation.
• Experience with Git and modern software development practices is a plus.