data engineer for customer data platforms
Summary
Senior data engineer at team.blue (posted via Enfint) designing customer-domain data products and scalable ETL/ELT pipelines across 60+ sub-brands. Core stack: Databricks (PySpark, Delta Lake, Unity Catalog), expert SQL, AWS/Azure, Airflow or dbt, Docker/Kubernetes, GitLab/GitHub CI/CD. On-site in Barcelona; mentoring and data governance are key responsibilities.
Описание
team.blue is a digital enabler for companies and entrepreneurs, providing innovative digital services through an ecosystem of hosting, SaaS, e-commerce, compliance, marketing, and collaboration brands across Europe.
Задачи
- Design and deliver scalable customer-domain data products that provide a unified source of truth across 60+ global sub-brands
- Build and optimize ETL/ELT pipelines for structured and unstructured data, ensuring high availability and low latency
- Lead the design of secure and cost-efficient data architectures
- Establish and enforce best practices in data modeling, orchestration, and observability
- Implement data governance frameworks covering lineage tracking, metadata management, and quality controls
- Translate complex business requirements into high-performing technical solutions for Analytics, ML, and AI teams
- Manage and tune data pipelines through indexing strategies, query optimization, and schema evolution
- Mentor junior engineering team members and foster technical excellence
- Lead projects from ideation to actionable solutions while balancing technical debt and rapid delivery
- Translate complex technical concepts into clear business value for non-technical stakeholders
- Manage multiple high-priority workstreams with attention to detail
Требования
- 7+ Years of professional experience in data engineering or data management
- Advanced degree (Masters or PhD) in Computer Science, STEM, or a related quantitative field
- Deep hands-on experience with Databricks (PySpark, Delta Lake, Unity Catalog) or very rich hands-on experience with open table formats
- Expert-level SQL skills, including optimization and indexing
- Mastery of dimensional, star schema, and snowflake data modeling techniques
- Proficiency with at least one major cloud provider, such as AWS or Azure
- Experience with Airflow or dbt
- Strong command of Docker and Kubernetes
- Commitment to CI/CD best practices with Gitlab or GitHub
- Experience with data versioning, schema evolution, and distributed metadata management
- Demonstrable history of deploying stable, high-performance data solutions that drive measurable business value
- Ability to communicate complex technical concepts clearly to non-technical stakeholders
Условия
Employment in Barcelona, Catalonia, Spain; Relocation packages and visa sponsorship are not available; Candidates must provide proof of eligibility to work in the country of application.
What they ask for
Required
- 7+ years of professional experience in data engineering or data management
- Advanced degree (Masters or PhD) in Computer Science, STEM, or related quantitative field
- Deep hands-on experience with Databricks (PySpark, Delta Lake, Unity Catalog) or very rich experience with open table formats
- Expert-level SQL skills, including optimization and indexing
- Mastery of dimensional, star schema, and snowflake data modeling techniques
- Proficiency with at least one major cloud provider, such as AWS or Azure
- Experience with Airflow or dbt
- Strong command of Docker and Kubernetes
- Commitment to CI/CD best practices with GitLab or GitHub
- Experience with data versioning, schema evolution, and distributed metadata management
- Demonstrable history of deploying stable, high-performance data solutions that drive measurable business value
- Ability to communicate complex technical concepts clearly to non-technical stakeholders
- Proof of eligibility to work in the country of application