Your Role:

As Data Engineer, you will be the primary owner of Dedale’s data stack. You will define how we govern, model, maintain, migrate, and enrich our data (proprietary and public data) - setting the foundation for everything from analytics to AI-powered products. Joining Data and Tech Teams of 20+ people, you will collaborate closely with our Product and Research Teams.

This is a high-impact, high-autonomy role, with a clear path toward Data Architect.

- Data Governance

• Define and enforce access policies: who can see what, who can change what – aligned with GDPR standards

• Implement data quality checks and completeness monitoring across all sources

• Build and maintain a data catalogue — making data discoverable and trustworthy

• Own data observability: detect anomalies, lineage issues, and freshness gaps proactively

- Data Architecture – in close coordination with our product team

• Design and maintain Dedale’s canonical data model — the single source of truth

• Own the full data pipeline: ingestion, transformation, storage, and serving layers

• Select and evaluate the right tools for each layer of the stack (ETL, warehouse, orchestration)

• Ensure coherence, consistency, and scalability as we grow

- Data Pipelines Automation and Enrichment

• Automate data workflows, reducing manual steps, improving reliability and building scale

• Design and build new pipelines that enrich raw data with external sources and computed signals

• Partner with analysts and product teams to deliver clean, ready-to-use proprietary datasets

- Data Modernisation & Migration

• Audit and progressively migrate legacy data infrastructure toward a modern, scalable architecture

• Identify technical debt in the data stack and drive its resolution methodically

• Ensure zero data loss and high availability during migration phases

Must-haves:

• 3 to 5 years of experience in a data engineering role

• Proficiency in Python and SQL

• Solid experience with data modelling, pipeline design, and warehousing (e.g. Airtable, dbt, Airflow, BigQuery, Snowflake, Spark)

• Interest and exposure to AI/ML pipelines and feature engineering

• Hands-on knowledge of data governance principles and tooling

• Track record of working in a start-up or scale-up environment — you thrive with ambiguity

• Entrepreneurial mindset: you see the big picture, propose solutions, and take ownership

Nice-to-haves:

• Experience with data migration projects

• Familiarity with data cataloguing and observability tools (e.g. DataHub, Monte Carlo, Great Expectations)

• Interest in growing into a Data Architect role — we will invest in your development

Who you are:

• You take pride in clean, reliable data and treat it as a product

• You communicate clearly with technical and non-technical stakeholders alike

• You balance speed with rigour — you can ship fast without cutting dangerous corners

• You are proactive, curious, and always looking for ways to improve the stack

What We Offer:

• High autonomy and direct impact from day one

• A clear career path toward Data Architect

• A collaborative, intellectually stimulating environment

• Competitive compensation package

• Flexible working arrangements

• Intro Call with a member of HR Team

• Interview with the Hiring Manager

• Case Study

• Final Interviews