The Role
Design, build, and maintain scalable cloud data pipelines, databases, and analytics platforms using Azure and Databricks. Integrate industrial/time-series data, develop ETL/ELT and API-based integrations, define data models and governance, and support analytics, AI-driven solutions, predictive maintenance, and operational reporting in collaboration with cross-functional teams.
Summary Generated by Built In
The Data Engineer is responsible for designing, developing, and maintaining scalable data pipelines, databases, and analytics platforms that support cloud-based digital applications for food and beverage processing plants. Working closely with Product Owners, Software Developers, Automation Engineers, and Process Experts, this role enables advanced analytics, AI solutions, predictive maintenance, asset performance monitoring, and operational reporting. This position can be based in Alcobendas (Spain), Naas (Ireland) or Bogota (Colombia), depending on the selected candidate.
Responsibilities / Tasks
- Design, develop, and maintain data solutions leveraging Microsoft Azure, Databricks, InfluxDB, Industrial IoT data sources, and modern data engineering practices.
- Design, develop, and maintain ETL/ELT pipelines to support data integration and analytics.
- Design data models, relationships, and schemas that support analytics, reporting, machine learning, and digital products.
- Develop API-based integrations using REST services and JSON.
- Establish standards for data quality, governance, security, and lifecycle management.
- Ensure data architectures are scalable, reliable, and aligned with enterprise standards.
- Support the integration of operational and equipment data from industrial systems into enterprise and cloud platforms.
- Collaborate with cross-functional teams to deliver data-driven solutions and enable business value through analytics and AI.
Your Profile / Qualifications
Educational Background
- Bachelor's or Master's Degree in Computer Science, Data Science, Engineering, or a related field.
- Microsoft Azure or Databricks Certifications.
- 3-7 years of experience in Data Engineering, Cloud Data Platforms, or Analytics Solutions.
- Experience developing Azure cloud-based data solutions.
- Experience working with large volumes of time-series and industrial data.
- Strong knowledge of:
- Data Modelling
- Data Governance
- Metadata Management
- Time-Series Database Design
- Query Optimization
- Workflow Orchestration
- REST APIs
- Proven experience working in Agile/Scrum environments.
- Awareness of IEC 62443 standards.
- Desirable knowledge of Machine Learning, AI, and Data Science concepts, with experience supporting AI-driven analytics solutions.
- Fluent English (B2/C1) required.
- Spanish or German would be considered a strong advantage.
- Strong ethics, compliance, and professionalism
- Commitment and alignment with business strategies and policies
- Customer-focused and sustainability-oriented mindset
- Cross-functional and multidisciplinary collaboration
- Excellent communication and networking skills
- Strong listening skills and cultural awareness
- Strong analytical, problem-solving, and decision-making skills
- Continuous improvement mindset and commitment to innovation
- Adaptability and willingness to learn new tools, technologies, and methodologies
We offer
Attractive compensation package aligned with experience & responsibilities
Private health insurance plan
Employee Assistance Program
Flexible working hours and a hybrid working model
23 days of vacation per year
Great work environment as part of a collaborative team
Continuous internal training and career development opportunities, both nationally and internationally
The opportunity to join a company recognized as a Top Employer 2026
Did we spark your interest?
Then please click apply above to access our guided application process.
Skills Required
- Master's Degree in Computer Science or a related field
- Microsoft Azure Certifications
- 3-7 years of experience in Data Engineering, Cloud Data Platforms, or Analytics Solutions
- Experience developing Azure cloud-based data solutions
- Experience working with large volumes of time-series and industrial data
- Experience with Databricks
- Experience with InfluxDB
- Design and development of ETL/ELT pipelines
- Design of time-series database schemas and query optimization
- Experience with REST services and JSON integrations
- Knowledge of data modelling, data governance, and metadata management
- Experience with workflow orchestration
- Proven experience working in Agile/Scrum environments
- Awareness of IEC 62443 standards
- Fluent English (B2/C1)
- Knowledge of Machine Learning, AI, and Data Science concepts
- Spanish or German language skills
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The Company
What We Do
GEA is one of the largest technology suppliers for food processing and a wide range of other industries. The global group specializes in machinery, plants, as well as process technology and components. GEA provides sustainable solutions for sophisticated production processes in diverse end-user markets and offers a comprehensive service portfolio
