About Inetum
Inetum is a European leader in digital services. For businesses, public sector organizations, and society as a whole, the group’s 26,000 consultants and specialists work every day to create tangible digital impact: solutions that contribute to performance, innovation, and the common good.
With a presence in 19 countries, working closely with local communities, and alongside its major software developer partners, Inetum supports organizations in their digital transformation challenges with proximity, flexibility, and responsibility. Driven by its purpose, Inetum champions a vision of technology that is useful and well-managed, capable of unlocking the full potential of organizations and society: “Let’s make tech right.”
In 2025, the group generated revenue of 2.2 billion euros.
More information at: www.inetum.com
Job Description:- Design, develop, maintain, and optimize data solutions on the Databricks platform.
- Build and manage end-to-end ETL/ELT pipelines using Databricks, PySpark, and SQL.
- Develop and maintain data ingestion, transformation, and publishing processes from multiple data sources.
- Implement and optimize Delta Lake structures, data models, and Data Lakehouse architectures.
- Develop Change Data Capture (CDC), historization, reconciliation, and data quality processes.
- Ensure data traceability, consistency, monitoring, logging, and operational support across the entire data lifecycle.
- Troubleshoot production incidents, perform data recovery activities, and ensure platform stability.
- Optimize processing performance, resource utilization, and platform costs.
- Contribute to development standards, automation, CI/CD practices, and technical best practices.
- Provide technical leadership, mentoring, and guidance to team members.
- 5+ years of experience in Data Warehouse, Big Data, or enterprise data platform development.
- 2–3+ years of hands-on experience with Azure Databricks.
- Proven experience delivering complex Data Warehouse, Data Mart, Data Lake, or Data Lakehouse projects.
- Strong expertise in PySpark, Advanced SQL, Delta Lake, Data Modeling, ETL/ELT processes, and Data Quality frameworks.
- Experience building and managing end-to-end data pipelines and orchestration solutions.
- Solid understanding of Data Lakehouse architecture, data governance, and data quality principles.
- Experience with Git, Jira, and modern software development practices.
- Ability to take full ownership of technical deliveries and drive solution implementation independently.
- Strong analytical, problem-solving, communication, and collaboration skills.
- Experience in the banking sector, including retail banking, financial reporting, risk, compliance, and regulatory reporting, is considered a strong advantage.
- Additional experience with Azure Data Factory, Kafka, Event Streaming, CI/CD, Unity Catalog, Machine Learning on Databricks, or Qlik Sense is a plus.
- Full access to foreign language learning platform
- Personalized access to tech learning platforms
- Tailored workshops and training to sustain your growth
- Medical insurance
- Meal tickets
- Monthly budget to allocate on flexible benefit platform
- Access to 7 Card services
- Wellbeing activities and gatherings
