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Role Overview
TAWANTECH is seeking a Senior Data Engineer to design, develop, and optimize scalable data platforms and pipelines within the banking and financial services domain.
Role Purpose
The Senior Data Engineer will build robust, secure, and scalable data solutions that support regulatory reporting, risk management, customer analytics, and business intelligence initiatives. The ideal candidate will have strong expertise in Python, SQL, big data technologies, and cloud-based data ecosystems.
Key Responsibilities
Pipeline Development and Optimization
- 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.
- Implement monitoring, troubleshooting, and performance tuning for data pipelines and processing frameworks.
Data Architecture
- Design and implement Data Warehouse and Data Lake architectures to support enterprise banking analytics and reporting requirements.
- Develop and maintain high-performance data models for transactional, customer, risk, and regulatory data.
- Leverage cloud platforms or Cloudera ecosystem technologies to build and manage modern data infrastructure.
Data Governance and Compliance
- Ensure data quality, governance, security, and regulatory compliance across data platforms.
- Support regulatory reporting, audit requirements, and data lineage initiatives.
Operations and Best Practices
- Drive CI/CD implementation and DataOps best practices to improve deployment efficiency and operational reliability.
Stakeholder Collaboration
- Collaborate with business stakeholders, data analysts, risk teams, and compliance teams to deliver data-driven solutions.
Team Leadership
- Mentor junior engineers and contribute to technical architecture and best practices.
Qualifications & Experience
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- 4+ years of hands-on experience in Data Engineering.
- Banking or Financial Services domain experience with exposure to financial data, regulatory reporting, risk, compliance, or customer analytics.
Skills & Competencies
- Strong programming skills in Python and advanced SQL.
- Expert-level experience with Apache Spark for large-scale data processing.
- Expert-level experience with Apache Airflow for workflow orchestration and scheduling.
- Solid understanding of Data Warehouse and Data Lake architectures.
- Strong knowledge of data modeling techniques and performance optimization strategies.
- Experience implementing CI/CD pipelines and DataOps methodologies.
- Experience working with cloud platforms (AWS, Azure, or GCP) or the Cloudera ecosystem.
- Excellent problem-solving, analytical, and communication skills.
Additional Information
Preferred Qualifications
- Experience with banking data domains such as Core Banking, Payments, Lending, Treasury, Risk, AML, KYC, or Regulatory Reporting.
- Knowledge of financial data governance, security, and compliance standards.
- Experience with real-time and batch data processing in highly regulated environments.
- Familiarity with containerization technologies such as Docker and Kubernetes.
- Experience with data lineage, metadata management, and data quality frameworks.
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