Data Platform Engineer

Supermetrics; Helsinki; On-site; EUR 65,000 - 100,000; Full time

Job summary

Supermetrics is seeking a Data Platform Engineer to build, run, and improve our internal data platform that powers ingestion, transformation, and delivery across the business. You will own pipelines, tooling, and systems used by every team, with AI integrated into development and operations.

We value experts in Python and SQL, Kubernetes, Airflow, and cloud platforms (GCP). You will influence architecture, contribute to governance tools, and build scalable, cost-aware solutions that support

Qualifications

• 3+ years of experience in platform engineering, data engineering, or infrastructure‑focused software development.
• Background in cloud platforms, especially GCP.
• Proficiency in Python and SQL.
• Experience developing, deploying, and managing data platforms and pipelines on Kubernetes.
• Experience with orchestration tools, specifically Airflow.
• Experience with CI/CD principles and tools.
• A genuine ownership mindset, treating the platform as a product for internal customers, not just a codebase to maintain.
• AI tools embedded in your core work, not something you dabble in occasionally.

Responsibilities

• Build core data platform components and services, working closely with Analytics and Data Governance.
• Develop and maintain event tracking infrastructure and data loaders.
• Implement data integrations using Datastream, custom pipelines, and Airflow.
• Operate MCP servers enabling AI agents to query governed data.
• Manage deployment workflows across Kubernetes, ArgoCD, and GitOps.
• Develop with Python, Kubernetes, and Infrastructure as Code; use AI to scaffold pipelines and generate tests.
• Contribute to analytics and governance tooling (dbt, Looker, OpenMetadata, data contracts).
• Support cloud cost attribution and IAM governance via Terraform, plus disaster recovery processes.
• Build automations using AI and agent technologies for measurable impact.
• Collaborate with dev teams on data collection and integration best practices.
• Participate in technical discussions shaping platform architecture.

Skills

Python

SQL

Kubernetes

Airflow

CI/CD

GCP

AI tools

Tools

Avo

dbt

Looker

OpenMetadata

Terraform

Job description

Supermetrics helps over 200,000 organisations make sense of their marketing data, and we process a significant share of global online ad spend along the way. Fast, reliable infrastructure isn’t optional for us, it’s what lets our customers trust their data, and what makes every other team’s work possible. As a Data Platform Engineer, you’ll help build, run, and improve the internal data platform that powers ingestion, transformation, and delivery across the business. Reporting to our Data Platform Lead, this is a role with real ownership of the pipelines, tooling, and systems every team at Supermetrics depends on, and AI is part of how we build, not a side experiment.

Responsibilities

• Core data platform components and services, working closely with Analytics and Data Governance.
• Our event tracking infrastructure, built on Snowplow/OpenSnowcat, custom data loaders, and tooling like Avo.
• Data integrations using Datastream, custom pipelines, and Airflow.
• MCP servers that let AI agents query our governed data layer, making data self‑serve for every employee.
• Deployment workflows across Kubernetes, ArgoCD, and GitOps.
• Building with Python, Kubernetes, and Infrastructure as Code, using AI‑assisted development for pipeline scaffolding, test generation, and DAG authoring.
• Contributing to analytics and governance tooling, including dbt, Looker, OpenMetadata, and data contracts.
• Supporting cloud cost attribution, IAM governance via Terraform, and disaster recovery processes.
• Building automations using AI and agent technologies that make a real, measurable difference.
• Collaborating with dev teams on data collection and integration best practices.
• Participating in technical discussions that shape where our data platform architecture goes next.

Qualifications

• 3+ years of experience in platform engineering, data engineering, or infrastructure‑focused software development.
• Background in cloud platforms, especially GCP.
• Proficiency in Python and SQL.
• Experience developing, deploying, and managing data platforms and pipelines on Kubernetes.
• Experience with orchestration tools, specifically Airflow.
• Experience with CI/CD principles and tools.
• A genuine ownership mindset, treating the platform as a product for internal customers, not just a codebase to maintain.
• AI tools embedded in your core work, not something you dabble in occasionally.