Senior/Lead Data Engineer

My client is looking for a Lead Data Engineer to define and drive the technical evolution of its corporate data platform , ensuring scalability, reliability, maintainability, and cost efficiency.

Key Responsibilities

• Databricks modernization: Lead the modernization of the Databricks infrastructure, including the migration of existing workloads towards Spark Declarative Pipelines and modern engineering patterns.
• Platform engineering: Design and implement key platform capabilities through hands-on development , build reusable frameworks, conduct code reviews, and establish engineering standards.
• Performance & cost optimization: Continuously improve Spark performance, cluster utilization, processing efficiency, and overall Databricks costs using data-driven insights and engineering best practices.
• Technical leadership: Act as a trusted consultant and technical authority , supporting engineering teams and stakeholders in solving complex data challenges and translating business requirements into robust technical designs.
• Delivery: Support sprint planning, backlog refinement, effort estimation, and deployment practices , ensuring alignment with product goals and stable environments.
• Innovation: Evaluate new technologies, promote automation and DevOps practices , and identify and reduce technical debt.

Required

• Education: University degree in a relevant technical field
• Experience: Several years in Data Engineering and Technical Leadership
• Data Platforms: Experience designing scalable and reliable data platforms
• Problem Solving: Strong analytical and problem-solving skills
• Agile: Experience working in agile environments
• Communication: Clear communication and stakeholder collaboration
• Leadership: Ability to set technical standards and guide engineering teams
• English: Fluent and confident
• Personality: Proactive, empathetic, and collaborative

Required Technologies & Proficiency

• Databricks: Advanced
• Apache Spark: Advanced
• Python: Advanced
• SQL: Advanced
• Delta Lake: Advanced
• Data Processing Architecture: Advanced
• Performance Tuning: Advanced
• Workload Management: Advanced
• CI/CD: Intermediate / Advanced
• DevOps: Intermediate / Advanced
• Testing & Code Quality: Advanced
• Observability & Monitoring: Advanced
• Automation: Advanced
• Technical Leadership: Advanced
• Spark Declarative Pipelines: Nice to have
• Databricks Asset Bundles: Nice to have

What You Can Expect

• Employment: Permanent employment contract ( UoP ).
• Benefits: Private healthcare, sports card, group insurance, company product discounts, and other financial benefits.
• Work-Life Balance
• Development: Training, mentoring, language learning, and international projects.
• Flexible Working: Flexible start times, hybrid model
• Culture: Company events, family-friendly activities, and career development opportunities.