Data Engineer
Job Title: Data Engineer (Offshore)
Role Purpose
Design, develop, and maintain scalable data pipelines and ETL processes to support analytics, reporting, and business intelligence solutions. The role focuses on transforming raw data into structured, reliable datasets for downstream BI consumption.
Key Responsibilities
- Develop and maintain data ingestion and transformation pipelines using Oracle Cloud Data Integration (or similar ETL tools).
- Design and implement data mappings, transformation logic, and data workflows.
- Build robust ETL/ELT processes to extract, transform, and load data into analytics/data warehouse layers.
- Prepare and structure datasets optimized for reporting and dashboard consumption.
- Ensure data quality, consistency, and integrity across pipelines.
- Monitor and troubleshoot data pipeline failures, performance issues, and data availability challenges.
- Collaborate closely with BI Developers and BA/BI Consultants to align data models with reporting requirements.
- Optimize data pipelines for performance, scalability, and efficiency.
- Document data flows, transformations, and technical specifications.
Required Skills & Experience
- 4–7+ years of experience in Data Engineering or ETL development roles.
- Hands-on experience with Oracle Cloud Data Integration (OCDI) or similar ETL platforms (Informatica, Talend, Azure Data Factory, etc.).
- Strong SQL skills with expertise in data transformation and optimization.
- Solid understanding of data modeling concepts (star schema, snowflake schema, normalization/denormalization).
- Experience building and managing ETL/ELT pipelines for analytics and BI solutions.
- Familiarity with data warehousing concepts and architectures.
- Strong problem-solving skills with attention to data accuracy and quality.
- Ability to work in offshore delivery models and collaborate with cross-functional teams.
Nice to Have
- Experience in finance or banking domain
- Exposure to cloud data platforms (Oracle Cloud, AWS, Azure)
- Knowledge of big data technologies (e.g., Spark, Hadoop)
- Experience with performance tuning and pipeline optimization
Key Competencies
- Analytical and structured thinking
- Attention to detail and data accuracy
- Collaboration and teamwork
- Ownership and accountability
- Adaptability in dynamic environments