Kenya Commercial Bank Limited is registered as a non-operating holding company which started operations as a licensed banking institution with effect from January 1, 2016. The holding company oversees KCB Kenya - incorporated with effect from January 1, 2016 - and all KCB's regional units in Uganda, Tanzania, Rwanda, Burundi, Ethiopia and South Sudan. It als...

Read more about this company

Data Engineer

Job Type

Full Time

Qualification

BA/BSc/HND

Experience

Location

Nairobi

Job Field

Data, Business Analysis and AI , ICT / Computer

Job Description

Build Data Pipelines: Design, develop, and maintain robust data pipelines to reliably ingest, process, and consolidate data from diverse sources at scale.

Data Modeling and Warehousing: Build and manage efficient data models, data warehouses, and data platforms to support BI and advanced analytics initiatives.

ETL/ELT Optimization: Develop and optimize ETL/ELT processes for maximum performance, scalability, reliability, and cost-efficiency.

Data Quality and Governance: Implement and enforce standards for data quality, security, and governance across all data assets.

Monitoring and Troubleshooting: Proactively monitor, troubleshoot, and tune data pipelines, and systems for performance and reliability.

Production Integration: Support the deployment and integration of machine learning models and analytical products into production and enable automation of solutions.

Requirements Collaboration: Collaborate with data scientists, analysts, and business stakeholders to understand requirements and deliver clean, reliable, and well-documented datasets.

Architecture and Strategy: Contribute to the overall data strategy, architecture design, and continuous process improvement initiatives.

Reporting and Metrics Automation: Develop and automate metrics, dashboards, and reports to monitor data governance trends, such as data quality.

Technical Documentation: Create and maintain comprehensive technical documentation on data pipelines, configurations, setups, and deployment of data solutions.

• Design, develop, and maintain robust data pipelines to reliably ingest, process, and consolidate data from diverse sources at scale.
• Build and manage efficient data models, data warehouses, and data platforms to support BI and advanced analytics initiatives.
• Develop and optimize ETL/ELT processes for maximum performance, scalability, reliability, and cost-efficiency.
• Implement and enforce standards for data quality, security, and governance across all data assets.
• Proactively monitor, troubleshoot, and tune data pipelines, and systems for performance and reliability.
• Support the deployment and integration of machine learning models and analytical products into production and enable automation of solutions.
• Collaborate with data scientists, analysts, and business stakeholders to understand requirements and deliver clean, reliable, and well-documented datasets.
• Contribute to the overall data strategy, architecture design, and continuous process improvement initiatives.
• Develop and automate metrics, dashboards, and reports to monitor data governance trends, such as data quality.
• Create and maintain comprehensive technical documentation on data pipelines, configurations, setups, and deployment of data solutions.