Principal Data Engineer (Tech Lead)

This is a highly strategic and hands-on leadership role, ideal for someone who enjoys operating at scale, solving complex data challenges, and leading high-performing engineering teams.

You will lead a team of Data Engineers responsible for designing, building, and scaling a next-generation data platform used across multiple business domains including operations, supply chain, analytics, and decision-making.

The environment involves massive volumes of data, complex global operations, and high-impact business use cases, making this role particularly suited to candidates experienced in enterprise-scale data ecosystems.

This position combines:

• Technical leadership
• Platform architecture
• Team management
• Strategic influence
• Hands-on engineering

What You’ll Be Doing

• Lead and mentor a team of Data Engineers in a global environment
• Define and evolve the company’s Data Platform strategy and architecture
• Design scalable, secure, and high-performance data solutions
• Drive best practices in Data Engineering, governance, scalability, and reliability
• Work closely with business and technical stakeholders to support data-driven initiatives
• Contribute hands-on to architecture and engineering decisions
• Help shape the future of the organization’s data ecosystem and operating model
• Influence data strategy across multiple business units and regions

What We’re Looking For

• 7+ years of experience in Data Engineering
• Previous experience leading engineering teams in complex environments
• Strong experience working with large-scale data platforms and high data volumes
• Proven ability to operate both strategically and hands-on
• Strong communication and stakeholder management skills
• Experience designing modern data architectures and scalable data pipelines

Technical Environment

We are open regarding cloud background — experience with AWS, Azure, or GCP is welcome. GCP exposure is a plus, but leadership, architecture experience, and seniority are the real priorities.

Typical stack includes:

• Cloud Platforms: GCP / AWS / Azure
• Data Warehousing: BigQuery, Snowflake
• Languages: Python, SQL
• Transformation Tools: dbt / Dataform
• Infrastructure as Code: Terraform
• Modern Architectures: Data Mesh, Lakehouse, CDC, Event-Driven Pipelines