Job Details
Job Type:
Full Time
Workplace Type:
On-site
Qualification:
Degree
Job Experience:
Mandatory
Job Location:
Nairobi County, Kenya
Closing Date:
Undisclosed
Salary:
Estimated: KES 35,000 - KES 300,000 / month
Other Pay:
Benefits
Job Purpose Statement
Responsible for developing, maintaining, and optimizing financial data infrastructure. This role involves designing robust ETL/ELT pipelines, ensuring data quality for financial reporting and collaborating with finance stakeholders to drive data-driven insights.
Key Accountabilities
- Develop dashboards and scorecards for performance monitoring using an array of tools including Power BI, OBIEE
- Data Pipeline & Infrastructure Development: Lead the design and implementation of scalable data pipelines and warehouses to process complex financial data using tools like SQL Server, Azure Data Factory, ADLS, or AWS equivalents.
- Financial Data Modeling: Build and maintain sophisticated data models, ETL procedures, and automated workflows to support financial reporting, regulatory compliance, and forecasting. Champion for a robust data architecture design.
- Stakeholder Collaboration: Act as a bridge between technical teams and finance stakeholders (e.g., Accounting, FP&A) to define requirements and deliver actionable insights.
- Data Governance & Quality: Ensure high data integrity, accuracy, and security of financial records. Implement data governance policies to adhere to compliance requirements.
- Maintain technical documentation (data dictionary, lineage, pipeline runbooks) to support reuse and auditability.
- Implement data validation, reconciliation and control frameworks
- Perform any other duties as assigned.
Qualifications
- Degree in Finance, Commerce, IT, Data Science, or related discipline. (Finance Department exposure is a plus.)
- Strong SQL and data modeling; experience with ETL/ELT and data warehousing concepts.
- Programming for data (Python preferred) and orchestration/automation mindset.
- Ability to communicate with finance stakeholders and convert requirements into data products.
Education and experience
- 3–5 years in data engineering / analytics engineering, ideally supporting finance or enterprise reporting.
- 2-3 years experience in the Banking industry.
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