Technical Project Manager - Databricks / Spark
Technical Project Manager in Zürich leading Agile delivery of a client's data platform built on Databricks and Apache Spark — overseeing pipelines, cluster usage, cost, governance, and coordinating engineers, architects, and business stakeholders.
- Compensation
- Not disclosed
- Location
- Zürich, Switzerland
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 10+ years
- Category
- Project management
- Posted
Skills
Must have
- 10+ years of technical project management experience in enterprise or cloud-based environments
- Proven experience managing projects on Databricks
- Solid grasp of Apache Spark concepts: job orchestration, DAGs, optimizations, cost-performance tradeoffs
- Strong understanding of cloud platforms (Azure and/or AWS) and DevOps principles (CI/CD, IaC)
- Demonstrated success delivering data platforms, data transformations, or cloud migrations
- Skilled in stakeholder engagement, risk management, and Agile delivery
- Exceptional communication skills – able to simplify complex technical concepts for business leaders
Nice to have
- Exposure to Delta Lake, MLflow, and Unity Catalog
Full description
We are seeking a highly skilled Technical Project Manager to lead the delivery of our client Applicative Platform, built on Databricks and Apache Spark. This role demands both technical fluency and project leadership, ideally with a background in cloud-native data platforms and Agile delivery. You will collaborate closely with platform engineers, architects, analysts, and stakeholders to ensure the successful and secure execution of a modern data platform.
THE ROLE
Agile Delivery: Manage delivery using Agile frameworks (Scrum/Kanban), drive sprints, retrospectives, backlog grooming, and iterative planning.
Databricks Program Oversight: Oversee pipeline execution, cluster usage, cost optimization, and platform governance within Databricks.
Technical Project Management: Coordinate cross-functional engineering teams using Apache Spark, Delta Lake, and cloud-native tooling (Azure/AWS).
Stakeholder Management: Act as the interface between business units and technical teams, translating requirements into actionable delivery plans.
Quality & Risk Management: Ensure deliverables meet high standards for performance, security, reliability, and governance.
Continuous Improvement: Identify and drive enhancements in delivery processes, platform scalability, and team collaboration.
Compliance Awareness: Understand and integrate data security, data governance, and regulatory best practices into delivery pipelines.
Requirements
10+ years of technical project management experience in
enterprise or cloud-based environments
Proven experience managing projects on Databricks, ideally
with exposure to Delta Lake, MLflow, and Unity Catalog
Solid grasp of Apache Spark concepts: job orchestration,
DAGs, optimizations, cost-performance tradeoffs
Strong understanding of cloud platforms (Azure and/or AWS)
and DevOps principles (CI/CD, IaC)
Demonstrated success delivering data platforms, data
transformations, or cloud migrations
Skilled in stakeholder engagement, risk management, and