We are seeking a highly skilled
Senior Data Engineer to design, build, and maintain scalable data pipelines for enterprise-grade data platforms within the
Risk & Compliance domain. The ideal candidate will have strong expertise in
PySpark, Python, and data engineering best practices, with a focus on data quality, governance, and security.
Key Responsibilities
- Design, develop, and optimize scalable data pipelines using PySpark and Python
- Build robust ETL/ELT workflows to process large volumes of structured and unstructured data
- Collaborate with data scientists, analysts, and business stakeholders to deliver high-quality datasets
- Ensure data integrity, accuracy, and reliability through validation frameworks and monitoring
- Implement data security and access control mechanisms aligned with compliance standards
- Work closely with Risk & Compliance teams to support regulatory and reporting requirements
- Optimize performance of data processing jobs and queries
- Maintain and enhance existing data architecture and pipelines
Required Skills & Experience
- 6+ years of experience in Data Engineering
- Strong hands-on experience with PySpark and Python
- Solid experience with SQL and Oracle databases
- Experience in building and maintaining large-scale data pipelines
- Good understanding of data warehousing concepts and ETL frameworks
- Experience with data validation, data quality, and governance frameworks
- Familiarity with cloud platforms (AWS/Azure/GCP) is a plus
- Exposure to banking, financial services, or risk & compliance domain is preferred
Key Competencies
- Strong problem-solving and analytical skills
- Ability to work in a fast-paced, collaborative environment
- Excellent communication and stakeholder management skills
- Attention to detail with a focus on data quality and security
Nice to Have
- Experience with Big Data ecosystems (Hadoop, Spark)
- Knowledge of data security and regulatory compliance frameworks
- Prior experience working with enterprise data platforms
