Data Engineer
Pubblicato il 26-10-2026 - Team in Roma
Our Business
team.blue is an ecosystem of successful brands working together across regions to provide customers with everything they need to succeed online. 60+ successful brands make up the group; with a team of more than 3000+ experts serving its 3.5 million customers across Europe and beyond.
team.blue's brands are a mix of traditional hosting businesses, offering services from domain names, email, shared hosting, e-commerce and server hosting solutions and specialist SaaS providers offering adjacent products such as compliance, marketing tools and team collaboration products. This broad product offering makes it a one-stop partner for online businesses and entrepreneurs across Europe.
Position Overview
As a Senior Data Engineer , you will develop and maintain our central data ecosystem, ensuring we extract maximum strategic value from our global data assets. You will be responsible for building, scaling, and governing high-value data products that serve as the "single source of truth" for team.blue and its 60+ subbrands. This role is pivotal in transforming raw data into a sophisticated semantic layer that powers business intelligence, operational efficiency, and cutting-edge AI initiatives.
Key Responsibilities
- Data Platform Ownership: Own, manage, continuously optimize our Data Infrastructure including Databricks, Airflow, dbt, Gitlab & AWS. Manage and tune data platforms for peak performance and introduce new capabilities to keep the platform aligned with industry advancements
- Data Product Innovation: Design and deliver high-quality,
scalable data products that provide a unified source of truth across a complex ecosystem of 60+ global sub-brands.
- Pipeline Engineering: Build and optimize robust ETL/ELT pipelines to ingest and transform massive volumes of structured and unstructured data, ensuring high availability and low latency for downstream consumers.
- Architectural Leadership: Lead the design of secure, cost-efficient data architectures. Establish and enforce best practices in data modeling, orchestration, and observability.
- Governance & Integrity: Implement rigorous data governance frameworks, including lineage tracking, metadata management, and quality controls to ensure a reliable semantic layer for AI and ML use cases.
- Cross-Functional Collaboration: Act as a strategic "sparring partner" for Analytics, ML, and AI teams, translating complex business requirements into high-performing technical solutions.
- Platform Optimization: Manage and tune data platforms for peak performance, focusing on indexing strategies, query optimization, and schema evolution.
- Mentorship: Elevate the collective expertise of the engineering team by mentoring junior members and fostering a culture of technical excellence.
Your Strengths
- Strategic Thinker: You don't just execute; you lead projects from ideation to actionable solution,
balancing technical debt with rapid delivery.
- Effective Communicator: You possess the ability to translate complex technical concepts into clear business value for non-technical stakeholders.
- Problem Solver: You thrive in fast-paced environments, managing multiple high-priority workstreams with meticulous attention to detail.
Technical skills required
- Core Ecosystem: Deep hands-on experience with Databricks (PySpark, Delta Lake, Unity Catalog).
- Advanced SQL & Modeling: Expert-level SQL skills (optimization, indexing) and a mastery of data modeling techniques (Dimensional, Star Schema, Snowflake).
- Cloud & Modern Data Stack: Proficiency in at least one major cloud provider (AWS, GCP, etc) and modern orchestration tools like Airflow or dbt.
- Database Diversity: Proven experience managing data across various RDBMS platforms (PostgreSQL, SQL Server, Oracle, etc).
- DevOps & Engineering: Strong command of Docker/Kubernetes and a commitment to CI/CD best practices.
- Governance: Experience with data versioning, schema evolution, and distributed metadata management.
Education and work experience
- Experience: 7+ years of professional experience in data engineering or data management, preferably within a high-growth or multi-brand industry.
- Education: Advanced degree (Masters or PhD) in Computer Science, STEM, or a related quantitative field.
- Track Record: A demonstrable history of deploying stable, high-performance data solutions that drive measurable business value.
Right to Work
At any stage, please be prepared to provide proof of eligibility to work in the country you