[Hiring] Data Analytics Engineer @Prodigy Finance Limited

Role Description

The Data team at Prodigy Finance owns the analytical data plane — the foundation for portfolio analytics, lender reporting, funding operations, and credit risk. A small, focused team manages a set of business-critical data systems including the Risk ETL, Loan Tape, and funding allocation infrastructure, all built on AWS Redshift and maintained through Python, SQL, and DBT.

You will join as a Data Analytics Engineer working alongside our Data Modelling and Data Engineering leads. Your primary focus will be on building and maintaining the ETL pipelines, data models, and reporting workflows that keep these systems running reliably. This is a hands-on execution role with real ownership — you will work through a backlog of meaningful technical improvements, support live systems, and help raise the overall quality and reliability of Prodigy's data infrastructure.

You will work in a team of four and closely collaborate with teams in Credit Risk, Capital Markets, Compliance, and Funding Operations who depend on this data every day.

Responsibilities

• Support the design and development of data solutions under the guidance of the Senior Engineers
• Work with AWS Redshift and related AWS technologies, using GitHub to manage and version ETL processes and pipelines
• Write, debug, and maintain SQL and Python code to build and sustain data models in the warehouse
• Adapt ETL code as source data evolves or new business requirements come in
• Document ETL designs, testing approaches, and results clearly and thoroughly
• Support the creation, maintenance, and testing of reports in Tableau and/or Metabase
• Assist with automated reporting workflows and other recurring analytical processes
• Interpret data, investigate anomalies, and help maintain data quality across the warehouse
• Actively leverage AI coding assistants to accelerate delivery and improve output quality

Qualifications

• 3+ years of hands-on experience in a data engineering or analytics engineering role
• Strong working knowledge of SQL — writing, debugging, and optimising queries against large datasets
• Experience with Python for data transformation and pipeline work
• Familiarity with AWS Redshift or comparable cloud data warehouse technologies
• Comfortable with GitHub workflows and version-controlled development practices
• Demonstrable use of AI coding tools (GitHub Copilot, Cursor, or similar) as part of day-to-day work
• Ability to work autonomously and take ownership in a fully remote, distributed team

Requirements

• Familiarity with DBT — experience building or maintaining DBT models would be highly valued
• Exposure to financial or regulated data environments
• Experience working with ETL pipelines in a production setting
• Familiarity with data quality monitoring or testing frameworks
• Experience working with reporting tools such as Tableau or Metabase

Benefits

• Competitive remuneration package
• Company contribution to healthcare/medical aid scheme
• Fully remote
• Generous leave policy (24 days annual leave + 1 day for every year worked to a max of 29 days, birthday leave, 6 months' primary caregiver / 2 months' secondary caregiver parental leave, 4 weeks sabbatical leave after 5 years of continuous service)