H

Data Analyst

HFCB Kenya Limited

Nairobi Full-time Banking, Finance & Insurance Software & Data Mid Level
Salary: Open / Negotiable

Posted 2 days ago

Deadline: Oct 09, 2026

About the Company

HFCB Kenya Limited is a company in the Banking & Financial Services sector, founded in 1965.

Job Description

The Data Analyst is responsible for transforming complex enterprise datasets into actionable business insights, interactive dashboards, and executive reporting solutions. Leveraging advanced Power BI capabilities, SQL, and data visualization best practices, the role holder will partner with tribe members and business stakeholders to interpret trends, monitor operational performance, and support data-driven decision-making across the Group. As a key member of Phase 2 of our tribe’s expansion, you will work closely with Big Data Engineers and Product Owners to turn our processed data assets into intuitive, high-impact business intelligence dashboards, enabling continuous visibility across our digital platforms and business units.

Key Responsibilities

  1. Design, build, and maintain interactive, high-performing Power BI dashboards, reports, and executive scorecards tailored to business requirements.
  2. Develop advanced DAX (Data Analysis Expressions) formulas, measures, and calculated columns for complex business calculations and time-intelligence analysis.
  3. Perform robust data modeling in Power BI using Star/Snowflake schema patterns, managing relationships, security roles (Row-Level Security – RLS), and performance optimization.
  4. Manage and administer Power BI Workspaces, app publishing, scheduled data refreshes, and gateway configurations.
  5. Extract, query, and analyze large datasets from relational databases, data warehouses, and data lakes using advanced SQL scripts.
  6. Perform ad-hoc data analysis to uncover underlying trends, patterns, anomalies, and operational insights to support strategic business decisions.
  7. Cleanse, blend, and reshape data from multiple disparate sources using Power Query (M Language) and SQL before model consumption.
  8. Optimize data processing workflows for enterprise scalability, performance, and fault tolerance.
  9. Implement parallel processing, distributed computing, and caching mechanisms to handle massive data workloads.
  10. Develop monitoring, logging, and alerting solutions to track the health, latency, performance, and availability of big data systems.
  11. Implement automated scaling, load balancing, and resource allocation mechanisms to optimize cluster utilization.
  12. Validate data accuracy, consistency, and integrity across BI reports by conducting thorough reconciliation against source systems.
  13. Implement reporting standards, consistent UI/UX design layouts, and brand-aligned dashboard templates across the organization.
  14. Ensure reporting practices strictly adhere to data governance policies, access controls, and customer privacy standards.
  15. Collaborate with Product Owners, Business Analysts, and Squad Leads to gather, translate, and refine business reporting requirements into functional technical specs.
  16. Translate complex data analytics into clear, compelling narratives and visual presentations for non-technical leadership and operational teams.
  17. Document data definitions, KPI calculations, reporting models, and user guides for self-service analytics adoption.
  18. Enterprise-grade interactive Power BI dashboards and self-service reporting tools deployed across business teams.
  19. Optimized Power BI data models built with proper DAX logic, star schemas, and efficient query folding.
  20. Automated daily/weekly/monthly dataset refreshes configured via enterprise gateways.
  21. Complex SQL scripts and views created for ad-hoc analysis, reporting tables, and data validation.
  22. Row-Level Security (RLS) frameworks established to ensure safe, role-based data access.
  23. Clear data lineage, KPI documentation, and BI user guides delivered.
  24. Identified operational bottlenecks, business growth drivers, and trend insights presented to stakeholders.

Requirements

  1. Bachelor’s degree in Computer Science, Data Analytics, Statistics, Information Technology, Business Intelligence, or a related quantitative field.
  2. PL-300 certification (Microsoft Certified: Power BI Data Analyst Associate) is highly desirable and considered an added advantage.
  3. 3-6 years’ experience as a Data Analyst or BI Developer, preferably within banking, fintech, telecom, or digital financial services.
  4. Proven track record of designing end-to-end, high-adoption Power BI solutions for enterprise business units.

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Job Details

Function
Software & Data
Industry
Banking, Finance & Insurance
Type
Full-time
Location
Nairobi
Experience
Mid Level
Salary
Open
Posted
Aug 10, 2026
Views
26
Deadline
Oct 09, 2026

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