Senior Data Engineer

Lifecheq; South Africa; Remote; ZAR 600,000 - 900,000; Full time

Job summary

A forward-looking tech company is seeking a Senior Data Engineer to build and optimize its analytics data layer. You will design real-time data pipelines and ensure data integrity while collaborating with cross-functional teams. The ideal candidate should have strong SQL skills and experience in Python, Clojure, or Scala. This role allows for remote work, subject to availability during core hours.

Qualifications

• Strong coding skills in Python, Clojure, or Scala; your code is clean, efficient, and production-ready.
• A rigorous, analytical mindset—you identify bottlenecks proactively and design solutions thoughtfully.
• Track record of building clean systems in high-ownership environments like startups or small technical teams.

Responsibilities

• Designing a real-time ingestion pipeline for event-sourced data streams.
• Defining a clear semantic model and restructuring existing views.
• Cleaning up pipeline logic to reduce latency and improve readability.

Skills

Excellent SQL skills

Strong coding skills in Python, Clojure, or Scala

Experience with distributed data processing technologies like Spark

Interest in functional programming

Analytical mindset

Experience with Databricks, Delta Lake, and AWS

Familiarity with Terraform or similar tools

Job description

Overview

Join to apply for the Senior Data Engineer role at Lifecheq.

You’ll take ownership of our analytics data layer and work closely with our Platform and ML squads. Your job is to build a fast, clean, and reliable system that integrates backend data from an event-sourced architecture, external services, and JSON-based event logs—then serves performant, well-modelled views to analysts, ML pipelines, dashboards, and the product frontend.

Responsibilities

• Designing a real-time ingestion pipeline for event-sourced data streams and JSON logs on S3 for low-latency performance.
• Defining a clear semantic model and restructuring existing views into a maintainable, well-layered architecture.
• Ensuring a reasonable compute budget and building structured views that can be safely used across analytics, reporting, and application layers.
• Cleaning up pipeline logic to reduce latency, improve readability, and lower cognitive load.

This work is central to unlocking productivity across the business. Success looks like an analytics foundation that’s predictable, fast, and easy to extend—powering dashboards to ML models. As the platform scales, there will be opportunities to extend this foundation—designing for higher data volumes, streaming complexity, and broader cross-team data needs.

Qualifications

• Excellent SQL skills and deep understanding of databases
• Strong coding skills in Python, Clojure, or Scala; your code is clean, efficient, and production-ready.
• Experience with distributed data processing technologies like Spark.
• A genuine interest in understanding the business and carefully modelling data for clarity and performance.
• A rigorous, analytical mindset—you identify bottlenecks proactively and design solutions thoughtfully.
• Interest in functional programming and experience with Clojure, Scala, or related ecosystems.
• Track record of building clean systems in high-ownership environments like startups or small technical teams.
• Experience working with Databricks, Delta Lake, and AWS.
• Familiarity with Terraform or similar infrastructure-as-code tools.

Working with us

LifeCheq values technical depth, autonomy, and clear thinking. You’ll be part of a small, capable team that enjoys solving hard problems together and takes pride in doing things properly. It’s a collaborative, engineering-driven environment where well-reasoned decisions carry weight and where your ideas will be taken seriously. There’s plenty of room to shape systems and standards—so long as they’re driven by sound reasoning and a clear-eyed view of trade-offs.

This is a fully remote role, and we ask for availability during our core hours (10:00 - 16:00 GMT+2).

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Information Technology