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