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Senior Data Analyst
Cape Town
About Our Client
Our client is a fast-growing African technology company solving one of the most consequential problems in the region's digital economy, at scale and in high-stakes environments. Their platform is trusted by some of the continent's most demanding institutions precisely because it works. Their analytics function is small and growing, with strong foundations already in place: an expanding data warehouse, established governance and data quality practices, and reporting the business relies on. The gap now is capacity, not groundwork, and this role exists to close it.
The Role
As Senior Data Analyst, you will turn the business's data into decisions it can act on with confidence. Business questions rarely arrive fully formed, so your craft is to shape a broadly worded question into something that can genuinely be answered, answer it well, and land that answer with the people who need to act on it.
This is a senior, hands-on role that sits close to both the business and the data platform. You will be as comfortable interrogating a messy dataset in the morning as presenting a customer engagement analysis to leadership in the afternoon. You will work the lifecycle end to end: framing the question, modelling and interrogating the data, drawing out the insight, and seeing the recommendation through to a decision and its adoption.
Our client cares more about how well you think, how clearly you communicate and how curious you are about how data is built than about the particular tools you have used before. Strong analysts come from many backgrounds and industries, and they would like to hear from all of them.
What Success Looks Like in the First Six Months
You own the core business and client reporting, and the definitions behind those numbers are documented, consistent and trusted across teams.
Recurring reporting that is currently rebuilt by hand runs to a schedule, with quality checks attached.
At least one piece of analysis you initiated, rather than were asked for, has changed a product, operational or commercial decision.
Product, engineering and commercial teams see you as the person to ask about what the data actually says.
Key Responsibilities
Reporting, Dashboards and Self-Service
Own end to end reporting for key business metrics, keeping definitions consistent and trusted across teams.
Build and maintain dashboards and self-service tools that let teams find and act on insight independently.
Own recurring client reporting from definition and automation through to quality assurance, delivery and follow-up, and be credible explaining a number or a discrepancy directly to a client's team.
Handle ad hoc requests with sound judgement: establish the real question, deliver a clear and actionable answer, and prioritise sensibly when several arrive at once.
Match the right reporting and visualisation tool to the audience, the question and the shelf life of the answer.
Product and User Behaviour Analysis
Analyse user behaviour across products to identify trends, friction points and opportunities, and turn findings into concrete recommendations.
Track and report on engagement, retention and customer journey metrics, flagging risks and opportunities proactively.
Apply appropriate statistical rigour, including cohort analysis, significance testing, forecasting and seasonality, so that recommendations hold up under challenge.
Design and evaluate experiments with the product team, being clear about what a result does and does not prove.
Investigate anomalies and work out whether what you are seeing is genuine signal, a data quality issue or noise.
Automation and Data Foundations
Automate recurring analysis and reporting so that regular outputs run reliably to a schedule with quality checks.
Build and maintain analytical models and reusable assets on top of curated data, so that knowledge compounds rather than living in one-off queries.
Specify what the analytics layer needs from upstream data (sources, structures, definitions and refresh frequencies) and work with engineering to deliver it.
Understand the data platform well enough to be a genuine partner to engineering: where data comes from, how it flows, and what an upstream change will mean downstream.
Data Governance, Quality and Privacy
Work responsibly with personal and sensitive data in line with POPIA and client obligations, applying least-privilege access, aggregation and de-identification as a matter of course.
Identify and resolve data quality issues at the source rather than patching around them downstream.
Apply sound data security, governance and metadata management practices across pipelines, dashboards and datasets.
Contribute to lean, practical governance standards that balance rigour with the team's pace of delivery.
Stakeholder Engagement, Mentorship and Documentation
Partner with product, marketing, engineering and operations to ensure data is accessible, accurate and used effectively.
Communicate technical and analytical concepts clearly to both technical and non-technical audiences.
Represent the analytics perspective alongside engineers, architects and leaders on the broader data platform roadmap.
Mentor junior and intermediate analysts as the team grows, and contribute to internal training and knowledge sharing.
Maintain clear documentation of data models, dashboards and workflows, so the team never depends on one person's memory.
AI-Augmented Ways of Working Use AI as a standard part of your workflow: exploring data, drafting and optimising SQL, building reports, writing documentation and pressure-testing your own analysis.
Build reusable AI workflows and share them with the team, turning repeatable analysis into dependable automation.
Keep a critical eye: verify AI output, know where it goes wrong, and never present a number you could not derive and defend yourself.
Stay current with a fast-moving tooling landscape and bring what you learn back to the team.
What You Will Bring
Experience and Qualifications
At least 5 years' experience as a Data Analyst or in a similar analytical role.
At least 5 years' BI and data visualisation experience. The team is deliberately tool-agnostic (Power BI, Looker, Tableau, Qlik or similar); what matters is that you have built things people actually use.
A track record of delivering analytical work independently in an agile, fast-paced environment, from scoping and estimating through to stakeholder sign-off, while managing competing priorities.
A Bachelor's degree in Mathematics, Statistics, Computer Science, Economics or a related field, or equivalent demonstrable experience.
Exposure to a regulated or high-integrity environment such as banking, insurance, telco, fintech, identity or risk is strongly advantageous.
Technical and Analytical Skills
Advanced SQL, and Python for analysis and automation.
Strong applied statistics, including cohort analysis, significance testing, forecasting and seasonality.
Experience with the Azure data stack (Data Factory, Synapse, Databricks) or an equivalent cloud data platform is valuable but not essential.
Familiarity with CI/CD, version control and modern development practices applied to analytics is advantageous.
Experience with monitoring and observability tools such as Application Insights, Azure Monitor or Grafana is a plus.
Governance, Communication and Ways of Working
A working understanding of data security, governance and metadata management principles, and comfort handling personal and sensitive data in a compliance-conscious environment.
Strong communication skills, with experience presenting your own analysis to senior stakeholders; experience presenting directly to external clients is advantageous.
Comfort owning work end to end, from framing a question through to seeing a recommendation adopted.
Experience supporting or mentoring less experienced analysts is a plus.
What's on Offer
Exclusive access to preferential financial benefits, including competitive rates on home loans, vehicle finance and personal loans.
A competitive compensation package designed to reward impact.
Enhanced family responsibility leave.
Annual leave entitlement that grows with your tenure.
A remote-first culture, with a preference for Cape Town based candidates.
A technically excellent, mission-driven team working at the frontier of its field, in a culture built on intellectual rigour, psychological safety, collaboration and a bias for action.
If you have not heard from us within one month of submitting your application, please consider your application unsuccessful. Due to the high volume of applications we receive, we are unable to respond to each applicant individually.
