Data Engineer
Role details
Job location
Tech stack
Job description
TheFork is looking for a Data Engineer to join our Core Data team in Bellprat, Spain. You will be responsible for designing and building data pipelines that will assist in transforming TheFork's data capabilities., We are looking for a Data Engineer to join our Core Data team as we transform TheFork's data capabilities through the implementation of a modern, self-service Data Platform (DPaaS).
In this role, you will design and build end-to-end data pipelines and contribute to evolving a platform that enables domain teams to autonomously produce and consume trusted data products. You will apply strong software engineering principles to data engineering, collaborate closely with platform stakeholders, and support the shift from a centralized BI model to a federated, domain-oriented data ecosystem. Key Responsibilities
- Design and implement high-quality, production-ready data pipelines following software engineering best practices (version control, CI/CD, testing, observability).
- Build data collection, ingestion, validation, and export pipelines for various sources using modern data stack tools.
- Contribute to the refactoring of existing orchestration design in Airflow to support scalability and maintainability.
- Contribute to technical POCs to evaluate new technologies and architectural approaches for the platform.
- Collaborate with Architects, Staff Engineers, and the Engineering Manager to validate and evolve the target data architecture.
Data Governance & Quality
- Implement data contracts and quality controls to ensure data products meet defined SLOs.
- Apply data modelling best practices including medallion architecture to create trusted, reusable data assets.
- Support the implementation of domain ownership models and single sources of truth per capability.
- Ensure data lineage, observability, and metadata management are embedded in all pipelines.
- Contribute to building a strong developer experience (DevEx) to enable engineering teams to adopt self-service data capabilities.
- Work closely with DataOps to leverage CI/CD pipelines and infrastructure-as-code practices.
- Collaborate with BI and analytics engineering teams, who are the primary users of the Data Platform.
- Support engineering teams in onboarding new data use cases onto the platform.
- Build strong cross-team relationships to facilitate adoption and continuous improvement of the platform., You will report directly to the Senior Data Engineering Manager and work in close collaboration with:
- DataOps team: who own the Data Platform infrastructure
- Architects: to ensure technical decisions align with enterprise architecture
- BI teams, Engineering teams and Data Science teams: who are the main consumers of the platform
What we offer you
- Flexible working environment (2 days home office per week + up to 4 total weeks additional flexibility during the summer period and in December to work fully remotely)
- Competitive fixed salary and bonus
- International teams and a multicultural environment spanning 10 offices across Europe
- Highly inclusive working environment
- Lifestyle benefits that can be used to reimburse expenses related to physical and leisure activities, family support, travel etc
- Continuous learning and development programs
- Free access to resources to support mental health
- Dedicated parental leave and caregiver leave policies (12 weeks fully paid)
- Life & Disability Insurance at no cost to the employee
- Amazing offices with dining, a coffee point on each floor, and leisure area
All hiring happens through our careers site and official email. We do not text or ask for payment during the hiring process. Please report any suspicious messages immediately.
Requirements
- Minimum 3 years of data engineering experience.
- Strong experience in designing and building data pipelines.
- Familiarity with monitoring or observability tools.
Responsabilidades
- Design and implement high-quality data pipelines.
- Build data collection, ingestion, and validation pipelines.
- Contribute to technical POCs for new technologies.
Conhecimentos
Python skills SQL Data modeling concepts Data validation practices Collaboration
Formação académica
Bachelor's degree in Computer Science or related field, * Strong Python skills for building and maintaining data pipelines.
- Advanced SQL and understanding of performance basics.
- Good understanding of data modeling concepts (including medallion architecture).
Data Platform & Warehousing
- Hands-on experience with Snowflake or another modern cloud data warehouse (e.g. BigQuery, Redshift, Databricks).
- Understanding of ELT patterns and how transformations are performed inside analytical warehouses.
- Familiarity with performance considerations such as partitioning, clustering, and query optimization basics.
Orchestration & Integration
- Experience using Airflow orchestration tool to design and maintain DAGs.
- Exposure to modern data integration tools (e.g. Airbyte) is a strong plus.
- Understanding of API-based ingestion, database connectors, and schema evolution handling.
- Practical experience with cloud services such as AWS S3 and IAM for instance.
- Familiarity with Infrastructure as Code (e.g. Terraform) is a plus.
- Understanding of CI/CD workflows and Git-based collaboration.
Data Quality & Reliability
- Awareness of data validation and testing practices.
- Experience working with monitoring or observability tools is a plus.
- Basic understanding of data governance concepts (PII handling, access control).
Execution & Autonomy
- Ability to break down complex technical problems into structured, actionable tasks.
- Strong ownership mindset with the ability to deliver end-to-end pipeline components.
- Product-oriented mindset with understanding of how data enables business value.
- Effective collaboration across engineering, product, BI, and data science teams.
- Eagerness to learn and continuously improve technical and platform knowledge.
Experience
Minimum 3 years of data engineering experience.
Benefits & conditions
The ideal candidate will have a strong background in Python, SQL, and experience with data warehousing. We offer flexible working conditions and a competitive salary alongside benefits to support your wellbeing and professional growth.