Job Description: Lead Platform Engineer Type of contract: Freelance Yearly B2B contract
We are looking for an experienced and hands-on Lead Data Platform Engineer to architect implement, and lead the delivery of a modern, self-service data platform, guided by the Data Mesh paradigm. This role is critical to enabling domain teams to build, deploy, and manage high-quality data products independently, enabling decentralized data ownership, and ensuring scalability, governance, and efficiency across the data ecosystem. You will serve as the technical lead, translator of needs, and strategic planner—bridging the gap between data product teams' pain points and platform capabilities. This role requires deep technical expertise in DevSecOps practices, Azure Cloud, Databricks, and modern data engineering practices. Architect and implement the data platform infrastructure end-to-end, including data ingestion, processing, quality, lineage, cataloging, security, and observability layers.
Define and execute a step-wise implementation roadmap for the self-service data platform—starting from core capabilities to advanced self-service tooling.
Engage deeply with data product teams to understand their challenges and translate those into platform features and reusable solutions.
Establish clear standards, patterns, and templates to accelerate the delivery of domain data products while enforcing consistency, governance, and quality.
Prioritize and manage the platform team's backlog, balancing business impact, scalability, and feedback from users.
Champion and implement the four core Data Mesh principles : domain-oriented ownership, data as a product, self-serve platform, and federated governance.
Unity Catalog, Role-Based Access Control) to protect sensitive data.
Drive the development and automation of onboarding processes for new domains and data products.
Lead architectural design reviews, technical roadmap planning, and hands-on engineering work with the team.
Mentor and guide data engineers working on platform and infrastructure components.
Proven experience architecting and building scalable, cloud-native data platforms on Azure Cloud and Databricks.
Deep understanding of modern data architecture patterns (e.g., Lakehouse, Data Mesh, Data-as-a-Product).
Data Lake Storage Gen2, Data Factory, Synapse, Event Hubs, CosmosDB, Azure ML etc.
Strong programming and scripting skills in Python and SQL; Experience integrating CI/CD pipelines for data products using tools like Azure DevOps or GitHub Actions.
Platform Design & Data Mesh Thinking:
Experience implementing the four principles of Data Mesh in real-world environments.
Expertise in designing data contracts, access patterns, and versioning mechanisms for data products.
Experience leading and mentoring platform engineers, shaping best practices, and driving architectural decisions.
Effective at leading a platform engineering team, conducting reviews, and ensuring delivery quality.
Ability to facilitate workshops and feedback sessions with data product teams and convert insights into technical requirements.
Background in implementing data platforms in regulated or enterprise environments.
Experience with observability and monitoring tools for data reliability (e.g.,