Senior Data Engineer

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for processing large volumes of banking and financial data
• Build and optimize data workflows using Apache Spark and Apache Airflow
• Design and implement Data Warehouse and Data Lake architectures
• Develop and maintain high-performance data models for transactional, customer, risk, and regulatory data
• Collaborate with business stakeholders, data analysts, risk teams, and compliance teams
• Ensure data quality, governance, security, and regulatory compliance
• Implement monitoring, troubleshooting, and performance tuning for data pipelines
• Leverage cloud platforms or Cloudera ecosystem technologies
• Drive CI/CD implementation and DataOps best practices
• Support regulatory reporting, audit requirements, and data lineage initiatives
• Mentor junior engineers and contribute to technical architecture

Requirements

• Bachelor's degree in Computer Science, IT, Engineering, or related field
• 4+ years of hands-on experience in Data Engineering
• Strong programming skills in Python and advanced SQL
• Experience with Apache Spark and Apache Airflow
• Solid understanding of Data Warehouse and Data Lake architectures
• Proven experience building and maintaining ETL/ELT pipelines
• Experience with cloud platforms (AWS, Azure, or GCP) or Cloudera ecosystem
• Strong knowledge of data modeling and performance optimization
• Experience implementing CI/CD pipelines and DataOps methodologies
• Banking or Financial Services domain experience

Preferred Qualifications

• Experience with banking data domains (Core Banking, Payments, Lending, Treasury, Risk, AML, KYC)
• Knowledge of financial data governance, security, and compliance standards
• Experience with real-time and batch data processing in regulated environments
• Familiarity with Docker and Kubernetes
• Experience with data lineage, metadata management, and data quality frameworks