Data Engineer

As a 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+ sub-brands. This role is pivotal in transforming raw data into a sophisticated semantic layer that powers business intelligence, operational efficiency, and cutting-edge AI initiatives., * Data Product Delivery: Build and maintain high-quality, scalable data products that support a unified source of truth across our global sub-brand ecosystem.

• Pipeline Development: Develop and optimize ETL/ELT pipelines to ingest and transform large-scale structured and unstructured data, ensuring reliability and performance for downstream users.
• Architecture Implementation: Contribute to the design of secure and cost-efficient data architectures while adhering to established best practices in data modeling and orchestration.
• Quality & Governance: Implement data quality controls, lineage tracking, and metadata management to ensure a dependable semantic layer for AI and ML applications.
• Team Collaboration: Partner closely with Analytics and ML teams to understand technical requirements and deliver high-performing data solutions.
• System Maintenance: Monitor and tune data platforms for performance, focusing on query optimization, indexing, and schema management.
• Process Improvement: Participate in code reviews and documentation to ensure high standards of engineering excellence across the team.

• Solution-Oriented: You are a proactive builder who can take a project from a requirement to a functioning solution, managing your time and tasks effectively.
• Strong Communicator: You can explain technical workflows and challenges clearly to both technical peers and business stakeholders.
• Analytical Thinker: You enjoy deconstructing complex data problems and building robust, automated solutions.

Technical Skills Required

• Core Ecosystem: Strong hands-on experience with Databricks (PySpark, Delta Lake, Unity Catalog).
• SQL & Modeling: Advanced SQL skills and a solid understanding of data modeling techniques (Dimensional, Star Schema).
• Modern Data Stack: Proficiency in at least one major cloud provider (AWS, GCP, Azure) and orchestration tools such as dbt or Airflow.
• Database Management: Strong experience working with various RDBMS platforms (e.g., PostgreSQL, SQL Server).
• Software Engineering: Familiarity with version control (Git), CI/CD workflows, and containerization (Docker).
• Data Integrity: Understanding of data versioning and schema evolution within a distributed environment.

Education and Work Experience

• Experience: 3-5 years of professional experience in data engineering or a closely related data-focused role.
• Education: Bachelor's degree in Computer Science, STEM, or a related quantitative field.
• Track Record: Proven ability to build and deploy stable data pipelines that improve data accessibility and business insights.

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.