Data Platform Engineer — Scale-Driven Distributed Systems

Sprint and Partners; Amsterdam; On-site; EUR 90,000 - 150,000; Full time

Benefits offered by this job

Relocation support

Conference & learning budget

Equity package

Job summary

Sprint and Partners is building a global fintech data platform with thousands of engineers, handling petabytes of storage and real-time decision-making. We hire engineers across mid, senior, and staff levels who enjoy building scalable tooling, frameworks, and infrastructure that powers data at scale.

You will work on distributed compute and storage, streaming infra, data quality tools, internal platforms, OLAP engines, and platform observability, using Python and the Hadoop ecosystem.

Qualifications

• Experience with distributed systems at scale.
• High-throughput data pipelines experience.
• Data infrastructure and platform engineering experience.
• Performance optimization and reliability engineering experience.
• Experience in private cloud or large-scale infrastructure environments.

Responsibilities

• Work on distributed compute and storage systems.
• Develop streaming infrastructure and event-driven architectures.
• Build data quality, validation, lineage, and governance tooling.
• Create internal developer platforms and self-service tooling.
• Design OLAP and analytical query engines.
• Improve platform observability, automation, and reliability.
• Use Python as the primary language.
• Leverage Kafka, Spark, Trino, Docker, and Hadoop ecosystem.

Skills

Distributed systems at scale

High-throughput data pipelines

Data infrastructure

Performance optimization

Reliability engineering

Private cloud / large-scale infra

Tools

Python

Kafka

Spark

Trino

Docker

Hadoop ecosystem

Job description

Sprint and Partners is building a global fintech data platform with thousands of engineers, handling petabytes of storage and real-time decision-making. We hire engineers across mid, senior, and staff levels who enjoy building scalable tooling, frameworks, and infrastructure that powers data at scale.

You will work on distributed compute and storage, streaming infra, data quality tools, internal platforms, OLAP engines, and platform observability, using Python and the Hadoop ecosystem.