Team Lead, Data Platform Engineering

Our Company:

At impact.com we are passionate about our people, our technology, and are obsessed with customer success. Working together enables us to grow rapidly, win, and serve the largest brands in the world. We use cutting edge technology to solve real-world problems for our clients and continue to pull ahead of the pack as the leading SaaS platform for businesses to automate their partnerships and grow their revenue like never before. We have an entrepreneurial spirit and a culture where ambition and curiosity is rewarded. If you are looking to join a team where your opinion is valued, your contributions are noticed, and enjoy working with fun and talented people from all over the world, then this is the place for you!

impact.com, the world’s leading partnership management platform, is transforming the way businesses manage and optimize all types of partnerships—including traditional rewards affiliates, influencers, commerce content publishers, B2B, and more. The company’s powerful, purpose-built platform makes it easy for businesses to create, manage, and scale an ecosystem of partnerships with the brands and communities that customers trust to make purchases, get information, and entertain themselves at home, at work, or on the go. To learn more about how impact.com’s technology platform and partnerships marketplace is driving revenue growth for global enterprise brands such as Walmart, Uber, Shopify, Lenovo, L’Oreal, Fanatics and Levi’s, visit www.impact.com.

Your Role at impact.com:

impact.com's Analytics Data Platform processes terabyte-scale data for one of the world's leading partnership SaaS platforms, covering the full lifecycle from ingestion to governed access.

We're looking for a technical people leader to own and grow the Data Platform Engineering team, while driving the architecture, reliability, and evolution of impact.com's Analytics Data Platform. This is a senior player-coach role: you'll combine hands-on technical leadership with direct people management, building a high-performing team, owning delivery, and shaping platform strategy. Expect to spend roughly 40% hands-on and 60% on leadership, people, and delivery, shifting as the team matures. You'll be accountable for both the team's output and its people, ensuring engineers are supported, challenged, and growing.

As Team Lead for Data Platform Engineering, you'll work across the full data ecosystem (ingestion, processing, storage, orchestration, access, and governance) using technologies like Scala, Python, Google Cloud Dataproc, BigQuery, and Airflow. You'll shape the operating model for the team, establish engineering standards, and drive platform strategy. This role is levelled at Senior/Staff Engineer on the engineering management track and reports to the Director of Advanced Analytics. The position is based in Cape Town, hybrid, with one day per week in office.

Data Platform Engineering is one of four sub-teams within the Data Analytics Group (DAG). DPE owns ingestion, infrastructure, orchestration, and platform services. Analytics Engineering owns the dbt transformation layer and semantic layer. Data Analytics owns reporting and insights. Data Product Management owns product roadmaps and governance processes. You'll partner closely with all three, but won't own dbt models, reporting, or product prioritisation directly.

Our ideal candidate combines distributed systems expertise with proven people leadership. Someone who can make architecture decisions, run a team, and translate platform trade-offs into business language. This role is for someone who wants to build both a platform and a team, not just maintain what exists.

What you'll inherit:

The platform has strong foundations: Scala/Spark pipelines processing TB-scale data, 37+ Fivetran connectors, Airflow on Astronomer for orchestration, a mature dbt-based transformation layer, and BigQuery as the core analytical warehouse. Databricks is part of the current stack but is being transitioned off in favour of Dataproc and BigQuery-native patterns. What's greenfield: governance frameworks, data contracts, SLOs/SLAs, observability, cost management, and data quality monitoring. You'll build the team that delivers on these opportunities.

What you'll do:

• Build and run a team of data platform engineers: set direction, re