Data Analytics Engineer focused on building ETL pipelines and data models at Prodigy Finance. Working with AWS Redshift, Python, and SQL in a hybrid team.
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
Requirements
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
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)
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