Data Platform Engineer
Posted 23 Jul 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 4+ yrs
- Management level
- Individual contributor
- Employment
- On-Site
No salary listed for this role.
Data Platform Engineer (Mid-Level)
Onsite Role - Office First
Team description
As part of the Platform tribe, we're building a self-service, AI-ready Data Platform that powers SumUp's next big bets: data, AI, and real-time analytics. Our team designs and runs the infrastructure that lets data engineers, analysts, and ML teams across the business ship reliable pipelines and products without reinventing the wheel each time. This role sits at the centre of that work, giving you a genuine chance to shape how thousands of SumUppers build with data every day.
What you'll do
- Build and evolve the data platform's infrastructure (Terraform, Kubernetes, GCP), so every environment is reproducible, version-controlled, and auditable
- Take end-to-end ownership of the reliability, performance, and scalability of the Data and AI platforms
- Develop self-service features, including for ETL and orchestration, so teams can move faster without bespoke integrations
- Automate operations to keep the platform highly available and cost-efficient as demand grows
- Evaluate emerging technologies and shape adoption strategies that improve platform capabilities and business outcomes
- Partner with product, infrastructure, data engineering, analytics, and AI/ML teams to make the standard path easier and safer than one-off integrations
You'll be great for this role if…
- More than 4 years of experience building internal platforms consumed by other teams, in a Data, Platform, or Software Engineering role
- Strong software engineering background in Python or Go, along with solid SQL skills
- Hands-on knowledge of infrastructure and containerisation, such as Terraform, Helm, Docker, and Kubernetes
- Comfort working with observability, monitoring, alerting, and platform reliability engineering practices
- Experience in modern data stack (dbt, Snowflake, Trino, Airflow, etc.)
- Track record of setting up SDLC practices for analytics teams, including Git workflows, CI/CD, testing, and documentation standards
It's OK if you don't meet 100% of these criteria. If you're missing a few, it just means you'll have room to learn and grow with us.
Nice to have:
- Real-time streaming experience (e.g. Kafka, Flink, StarRocks, Pinot, Druid, ClickHouse)