Senior Data Engineer

AWS, Kafka, Spark

Join a senior data team building and evolving large-scale AWS data pipelines that power security products protecting home networks at massive scale.

Start

2026-09-01

Duration

4kk +

Location

Helsinki, Hybrid, remote

Allocation

100%

This is a full-time 6+ month assignment starting in September, with hybrid work: one day per week on-site in Keilaranta and otherwise remote. The team is looking for senior support to accelerate feature development, improve an evolving AWS-based data platform, and help tackle large-scale ETL and streaming challenges in a security-focused product environment.

In this role, you will:

Design, develop, and operate high-volume batch and streaming data pipelines on AWS cloud-native infrastructure.
Work hands-on with technologies such as Kafka, Spark, Lambda, S3, Python, SQL, and Terraform/Terragrunt to deliver new features and platform improvements.
Help modernize data processing and warehousing capabilities by addressing scaling bottlenecks, ETL performance challenges, and architectural improvements.
Collaborate closely with a small senior team to reduce backlog, improve reliability, and support the development and maintenance of data products.
Contribute ideas that shape engineering practices, tooling, and platform evolution in an agile and supportive environment.

You will thrive if:

You bring strong senior-level experience building data platforms on AWS, especially with distributed processing and large-scale data pipelines.
You are comfortable working with streaming architectures and tools such as Kafka and Spark, and understand the realities of production-scale data systems.
You have solid hands-on skills in Python, SQL, infrastructure as code, and CI/CD practices.
You enjoy solving performance and scalability challenges, and can bring proven approaches rather than learning the fundamentals on the job.
You value collaboration, communicate clearly in English, and like working in a team where good ideas are heard and acted on.
Nice to have: Experience with utilizing AI in your own work

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