Data Analyst

• PositionData Analyst
• CompanyEcobank Uganda
• LocationKampala, Uganda
• Job TypeFull-Time
• CategoryBanking Jobs in Uganda
• IndustryBanking & Financial Services
• Job Identification1472
• Experience5-7 Years
• DeadlineWednesday, 1st October 2026

Ecobank Uganda Limited is a subsidiary of Ecobank Transnational Incorporated (ETI), the pan-African banking group headquartered in Lomé, Togo, which operates in 33 countries across Africa with additional offices in Beijing, London, Dubai, and Paris. Ecobank Uganda began operations on 19 January 2009 and is led by Managing Director Grace Muliisa, with its headquarters at Plot 8A, Kafu Road, Kampala.

The Data Analyst will work across the full data lifecycle at Ecobank Uganda: sourcing, cleaning, processing, analysing, and reporting on structured, semi-structured, and unstructured data to support business performance, client experience, strategy execution, and decision-making. You will apply data mining techniques, perform statistical analysis on large datasets, validate results through A/B testing and scenario modelling, and develop customer behaviour predictive models in collaboration with stakeholders.

This is a senior-level data role (5-7 years required) that goes well beyond basic reporting. You will lead the development of dashboards and performance fact sheets in Power BI, write SQL queries daily, use Python and R for statistical and predictive modelling, quality-assure work by junior analysts, develop data strategy and governance policies, and drive consistent standards for data management and analysis tools. You will also collaborate with data engineers on source data quality, work with database design teams on schema translation, and leverage AI as an analytics transformation tool. If you want to own data at a pan-African bank in Uganda, this is the role.

Business Needs Analysis

• Receive requests for data, engage and collaborate with internal and external stakeholders to understand business data requirements, and proactively interrogate stakeholders to ensure that performance data are delivered in an appropriate format and to the desired specifications.

Data Sourcing

• Identify and evaluate alternate, available, and relevant data sources to ensure reliability, validity, and simple, efficient access to appropriate source data.
• Locate and remove duplicate sources of data and download and store required data resources in a chronological structure.
• Work with other analysts and data engineers on quality assurance of source data and systems.

Data Cleaning

• Identify and resolve any ad hoc and persistent data quality and integrity issues by conducting both routine and ad-hoc data cleaning and testing, to facilitate the generation of aggregate and up-to-date performance data in a timely manner while meeting the principles of accuracy, integrity, completeness, and adaptability.

Data Processing

• Perform data pre-processing (data manipulation, transformation, normalisation, standardisation, visualisation, and derivation of new variables/features), as applicable to developing specific algorithms or models.
• Build rules to transform data into normalised data and report formats, depending on the needs of Model Development.
• Compile, sort, and organise data in preparation for subsequent analysis.

Data Analysis

• Discover and apply insights from big data sets of structured, semi-structured, and unstructured data to support business performance, client experience, overall execution of the strategy, and decision-making.
• Apply data mining techniques, perform statistical analysis on large data sets, and validate analysis using appropriate techniques (applying test data sets, A/B testing, scenario modelling, etc.).

Stakeholder Engagement

• Form productive networks with internal and external stakeholders.
• Collaborate to develop or enhance existing customer behaviour predictive models to meet specific business needs.
• Work with data analysis colleagues across the group to review, approve, produce, or update system or object data models and correlate these with bank models.
• Work with database design or administration teams to translate object and data models into appropriate database schemas within design constraints.

Quality Assurance

• Ensure all data solutions are delivered within required standards and agreed timelines.
• Quality-assure work completed by junior colleagues, including code and performance reports developed and supporting documents.
• Review work done by data analysts to assure compliance with standards, methods, and tools used in the bank for business information such as Power BI, SQL, etc.

Reporting

• Lead, develop, and generate routine and ad-hoc reports, dashboards, and performance data fact sheets in line with business requirements (in the required formats and with the relevant visualisations and commentary).
• Prepare interpretation of findings into clear, actionable, and timely insights and present these to internal and external clients.

Data Strategies, Policies, Procedures, Systems Standards, and Tools

• Develop and document policies, data strategy, procedures, governance guidelines, and SLAs.
• Comply with all applicable policies, standards, systems, processes, and procedures and technical policies so that all relevant data and governance requirements are fulfilled while consistently delivering quality banking services.

Data Stewardship

• Drive consistent standards for data management and analysis tools and techniques, and ensure business data needs for structured and unstructured data are consistently met.
• Ensure that strong controls are in place to deliver data that is fit for purpose within the business.

Required Education

• Minimum requirement is a Bachelor’s degree in Business, Statistics, Business Computing, Information Technology, Information Systems, Computer Science, or a related field.

Technical Proficiency

• Power BI, SQL, Python, and R experience.

Work Experience

• Five to seven (5-7) years collecting and analysing critical business data, transforming data, and maintaining high levels of integrity in data management. Data sharing, sourcing data from third parties for validation purposes, and service delivery of analysed critical data to business.
• Five to seven (5-7) years of experience and daily usage of Structured Query Language (SQL) and other common programming languages. Highly advanced computer skills are required.
• Five to seven (5-7) years of experience with and understanding of financial and non-financial performance data and terminology within banking. Understands bank products and services and business processes.

Technical Skills

• Data Analysis & Statistical Modelling: Ability to analyse statistics and other data, interpret and evaluate results, apply data mining techniques, perform statistical analysis on large datasets, and validate through A/B testing, scenario modelling, and test datasets.
• SQL & Programming: Daily usage of SQL with proficiency in Python and R for data manipulation, statistical analysis, predictive modelling, and automation.
• Business Intelligence & Visualisation: Experience with Power BI for building dashboards, performance reports, and data fact sheets with relevant visualisations and commentary.
• Data Integrity & Governance: Ability to ensure accuracy, consistency, and security of data throughout its lifecycle, and to develop data strategy, policies, governance guidelines, and SLAs.
• Metadata Management: Knowledge of IT systems and processes for sharing, storing, and retrieving information across the organisation.
• Code Writing & Review: Ability to write programming code based on prepared designs and quality-assure code written by junior analysts.
• AI & Machine Learning: Ability to leverage AI as an analytics transformation tool for predictive models, client engagement, and operational enhancement.

Soft Skills

• Articulating Information: Effectively expressing ideas and concerns, giving presentations, explaining findings to non-technical audiences, and showing confidence in interactions with stakeholders.
• Challenging Ideas: Questioning assumptions, challenging established views, and arguing personal perspectives to catalyse change and improve data-driven decision-making.
• Functional Analysis & UAT: Skills in analysing and translating client needs and testing system function against functional requirements.
• Stakeholder Engagement: Ability to form productive networks with internal and external stakeholders and collaborate on predictive models, data models, and database schemas.

Ecobank Uganda offers a competitive compensation package as part of a pan-African banking group operating in 33 countries. You will work within the Strategy & Enterprise Data Office, gaining exposure to group-wide data standards, AI-led analytics, and cross-border data collaboration. The bank’s recent milestone of crossing UGX 1 trillion in assets signals strong growth momentum, and your work will directly shape how data supports business performance, client experience, and strategic execution across the institution.

• Own the full data lifecycle at a pan-African bank: sourcing, cleaning, processing, analysing, reporting, and governance, not just one slice of the pipeline.
• Work within Ecobank’s 33-country network, gaining exposure to group-wide data standards, cross-border analytics, and pan-African banking data that few single-country roles can offer.
• Ecobank Uganda just crossed UGX 1 trillion in assets, meaning the data volumes and complexity are scaling rapidly, creating the kind of analytical challenges that accelerate your career.
• The role explicitly includes AI as a competency, positioning you at the forefront of analytics transformation in Ugandan banking.
• Lead and quality-assure junior analysts’ work, giving you people leadership and mentoring experience alongside your technical responsibilities.
• Develop data strategy, governance policies, and SLAs, building strategic and governance skills that elevate you beyond a purely technical data role.
• Use Power BI, SQL, Python, and R daily in a banking environment, building a tool stack that is in high demand across financial services globally.

Apply online through the Ecobank Professional Careers portal before the deadline of Wednesday, 1st October 2026. Use Job Identification 1472 to find the position:

Apply on Ecobank Careers Portal

Only shortlisted candidates will be contacted. Ecobank does not charge any fee at any stage of the recruitment process. NextRoleHub never charges for job applications. If anyone asks for payment, report them immediately.

• Demonstrate your SQL proficiency with specifics: the advert requires 5-7 years of daily SQL usage. Describe the databases you have queried (Oracle, SQL Server, PostgreSQL), the complexity of your queries, and the business problems they solved.
• Show your Power BI dashboard experience: name the dashboards you have built, the data sources they pull from, and how stakeholders used the outputs for decision-making.
• Highlight your banking data experience explicitly: the advert requires 5-7 years of understanding financial and non-financial performance data within banking. Reference specific banking metrics, products, and processes you have analysed.
• If you have built predictive models (customer behaviour, credit risk, churn, etc.) using Python or R, describe them in your application. The role specifically mentions customer behaviour predictive models.
• Mention your experience with data governance, quality assurance, and code review, as this role includes QA of junior analysts’ work and development of data strategy and policies.
• The deadline is Wednesday, 1st October 2026 (the advert notes “03:00 AM” as the portal cutoff). Apply well before that to avoid last-minute system issues.