> Markdown version of [/jobs/ext/3733110-lead-azure-data-engineer-madrid-remote-12-months](https://www.wearedevelopers.com/jobs/ext/3733110-lead-azure-data-engineer-madrid-remote-12-months). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Lead Azure Data Engineer - Madrid (Remote) - 12 months

- **Company:** Global Enterprise Partners
- **Location:** Madrid, Spain
- **Contract:** Temporary contract
- **Skills:** Microsoft Azure, Big Data, Business Systems, Cloud Database, Continuous Integration, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Systems, DevOps, Performance Tuning, Azure Data Lake, Technical Data Management Systems, Enterprise Data Management, Data Processing, Data Ingestion, Azure Data Factory, Microsoft Fabric, Deployment Automation, Data Management, Azure Synapse Analytics, Data Pipelines, Databricks
- **Published:** October 14, 2026
- **Apply:** https://www.globalenterprisepartners.com/en-gb/job/lead-azure-data-engineer---madrid-remote---12-months/4077619

## About the Role

* Minimum 5 years of experience in Data Engineering.
 * Strong expertise in Azure Data Lake, Azure Databricks, Azure Synapse Analytics, and/or Microsoft Fabric.
 * Extensive experience delivering enterprise ETL/ELT solutions.
 * Strong understanding of data architecture and large-scale data transformation initiatives.
 * Proven track record in data quality, governance, monitoring, and performance optimisation.
 * Experience with DevOps and CI/CD principles within data engineering environments.
 * Previous technical leadership experience within enterprise data teams.
 * Must be based within the European Union.

Manufacturing Data Experience

Candidates must demonstrate hands-on experience working with manufacturing and operational datasets, including one or more of the following:

 * Production and operational reporting
 * Manufacturing Execution Systems (MES)
 * Supply chain and inventory management data
 * Quality management and traceability data
 * Industrial IoT and sensor-generated data
 * Plant performance and operational analytics
 * ERP-to-manufacturing data integrations

Experience gained in manufacturing, industrial production, chemicals, mining, metals, building materials, or other asset-intensive industries is highly desirable.

Candidate Profile

 * Strong hands-on technical leader with excellent problem-solving abilities.
 * Able to bridge the gap between business requirements and technical delivery.
 * Comfortable working with both operational and IT stakeholders.
 * Experienced in delivering large-scale cloud and data transformation initiatives.
 * Strong communication and stakeholder management skills.

## Description

We are seeking an experienced Lead Industrial Data Engineering Consultant to support the delivery of a strategic data modernisation programme within a manufacturing-focused environment. The successful consultant will be responsible for designing scalable Azure-based data solutions and enabling the organisation to leverage operational, production, and supply chain data more effectively.
This role requires a strong understanding of both modern cloud data platforms and manufacturing data landscapes, as the consultant will be working with data generated across industrial operations and business systems.
Please note: Candidates must already be based within the European Union. Applications from candidates located outside the EU cannot be considered., * Design, develop, and maintain scalable data ingestion and transformation solutions within the Azure ecosystem.

 * Build enterprise-grade data pipelines that support analytics, reporting, and operational decision-making.
 * Integrate and harmonise data from manufacturing and business systems, including production, quality, supply chain, ERP, MES, and IoT platforms.
 * Optimise data processing, storage, and performance across cloud-based data environments.
 * Establish and promote best practices for data engineering, governance, and quality management.
 * Support the implementation of CI/CD standards and deployment automation for data solutions.
 * Work closely with business, operations, and technical stakeholders to understand requirements and translate them into scalable solutions.
 * Provide technical leadership and mentorship to data engineering teams.