Senior Data Engineer

Job Description

CRDB Bank Plc is a leading financial institution in Tanzania undergoing rapid digital transformation, with strong investment in data engineering, analytics, and real-time digital banking platforms. The Bank leverages large-scale data systems to enhance customer experience, improve operational efficiency, and support data-driven decision-making across all business units.

The Senior Data Engineer role is a key technical position responsible for building and maintaining scalable, high-performance data pipelines that transform raw digital banking data into structured, reliable, and analytics-ready datasets. The role ensures seamless data flow across mobile banking, internet banking, and payment systems to support business intelligence, reporting, and machine learning initiatives.

Responsibilities

• Design, build, and optimize scalable batch and real-time data ingestion pipelines using PySpark and distributed computing frameworks
• Develop and maintain enterprise-grade data lakes and data warehousing systems for large-scale banking data
• Build resilient ETL/ELT pipelines capable of handling failures, spikes, and network interruptions
• Implement and manage data storage formats such as Parquet and Delta Lake for efficient querying and processing
• Optimize query performance, data models, and storage structures to ensure low-latency analytics
• Design and enforce data contracts, schema registries, and data validation frameworks
• Implement data quality checks to detect and prevent upstream data issues affecting downstream systems
• Maintain data lineage, metadata cataloging, and documentation across all data systems
• Ensure compliance with banking data privacy, security, and regulatory requirements
• Implement data masking, encryption, and role-based access controls for sensitive information
• Deploy and manage data pipelines in containerized environments using Docker and Kubernetes
• Support orchestration tools such as Apache Airflow and other scheduling frameworks
• Collaborate with BI, Data Science, and Digital Banking teams to translate requirements into scalable data solutions
• Apply best practices in SQL optimization, Python development, and version control using Git
• Participate in code reviews, documentation, and continuous improvement of data engineering standards

Qualifications Required

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Data Science, Statistics, Mathematics, or related field
• Minimum of 3 years of professional experience in Data Engineering or database development
• Strong experience building and maintaining production-grade data pipelines
• Advanced proficiency in PySpark and Apache Spark ecosystems
• Expertise in ETL/ELT processes for large-scale datasets
• Strong SQL skills including query optimization, indexing, and data modeling
• Experience with relational databases such as PostgreSQL or Oracle
• Solid understanding of data lake architectures, Hive Metastore, and metadata management systems
• Hands-on experience with Docker, Kubernetes, and workflow orchestration tools like Apache Airflow
• Strong problem-solving ability and attention to detail
• Excellent technical communication and collaboration skills
• Ability to work independently and within cross-functional teams

General Conditions

• Full-time position based in Dar es Salaam, Tanzania
• Competitive and negotiable remuneration package
• Candidates must be eligible to work in Tanzania
• Role involves collaboration with multiple technical and business teams
• Applicants may undergo technical assessments and background checks
• Only shortlisted candidates will be contacted

How to Apply

• Applications must be submitted online via: https://careers.crdbbank.co.tz/jobs
• Upload an updated CV and relevant academic/professional certificates
• Ensure all information is accurate before submission
• Submit applications before 30 June 2026

Conclusion
This role is suited for experienced data engineering professionals who excel in building scalable, reliable, and secure data infrastructure. It offers the opportunity to work on high-impact digital banking systems supporting analytics, reporting, and machine learning at enterprise scale.