Senior Data Engineer

Job Description

At WithSecure™, we protect businesses all over the world. Our SaaS solutions safeguard against modern cyber threats, and our innovative Co-security approach reflects our belief that true protection requires collaboration and shared expertise. No one can solve every cyber security problem alone. Our vision is to become Europe’s flagship in cyber security. Every day, our talented teams work to prevent cyber extortion, secure critical infrastructure, and prevent misuse of sensitive data. At WithSecure, it’s our people who make us exceptional – a diverse community that values passion, purpose, and a commitment to workplace well-being. If you’re ready to make an impact with a company that’s transforming cybersecurity, we’d love to hear from you.

Withsecure is moving to an AI-native operating model and this role is the engineer who joins the data & AI team who builds it. You co-own the data products our AI projects depend on, making them reliable, well-governed and consumable by both humans and AI agents. You also design and build the automations and agentic processes that take manual work out of business operations.

This is not a ticket-taking engineering role. It sits where three things meet: business domain depth, modern lakehouse engineering and hands-on LLM/agent engineering in production.

Key Responsibilities

• Manage the data products that AI projects and reporting rely on: keep them accurate, documented, tested, and production-grade

• Drive the AI-native transformation: work with the business to identify where agents and automation genuinely replace manual work, then build and operate it

• Run AI agents in production: data-quality triage, reporting and conformance agents with observability and evaluation harnesses. You'll extend them, tune them, and design new ones using AI-assisted engineering tooling daily

• Act as the technical counterpart for the business in discovery, challenge requirements, prototype fast and turn approved prototypes into governed, automated processes

• Keep business-critical data products fresh and correct during critical reporting windows, explain drift to the underlying detail level and automate the recurring reporting pack

• Support the data & AI team with data modeling and pipeline topics and review work across the domain

What are we looking for?

• Business domain depth: several years working with the domain the data products serve.

• Translation skill: you can take a business stakeholder's half-formed question and turn it into a data product without a spec, then spar with the business on what the number should actually mean

• Databricks or similar data platform (Snowflake, MS Fabric) + dbt in production: medallion architecture, dbt models, tests, seeds and the semantic layer

• Dimensional modeling: star schemas, SCD2, surrogate keys, incremental strategies, late-arriving data handling

• A proven AI track record: you have shipped agents or LLM workflows in production, eval harnesses for AI outputs or substantial AI-accelerated engineering to show for it

• Software discipline: Git feature-branch workflow, CI/CD, code review, documentation as part of done

Bonus points

• AWS data stack: Bedrock, Lambda, IAM/OIDC patterns

• Terraform and infrastructure-as-code for data platforms

• Data quality engineering: statistical anomaly detection, reconciliation harnesses, metric governance / certification of "one canonical number"

• Governance: GDPR-grade masking and pseudonymization in a data platform context

• BI and orchestration tooling: modern BI platforms, Databricks Asset Bundles, event-driven pipelines, multi-environment promotion

If you don’t tick every box above, don’t worry — we’re more interested in your potential and willingness to learn.

The salary displayed on this page represents the starting point for the role. Final compensation is discussed individually and depends on experience, skills, and the local market.

What will you get from us

• Meaningful work with real-world impact – your work helps protect businesses and critical infrastructure from modern cyber threats.
• Flexible ways of working, including up to 30 days per year working abroad and paid sick leave from day one.
• A strong focus on well-being, with mental health support and comprehensive benefits.
• Continuous learning, modern tools, and a people-first culture that values trust and collaboration.