Team Lead, Data Engineering

The role

You will lead a team of two data engineers and own the data platform, roadmap, and technical direction. You will act as a player-coach, staying hands-on to ship code and make architectural decisions for systems involving Snowflake, Azure, and dbt.

What you will do

• Lead a team of two data engineers through outcomes and goal setting
• Run regular 1:1s and provide feedback and development
• Partner with Product, Engineering, Customer Success and GTM to shape the roadmap
• Make technical direction and architectural calls
• Manage Snowflake performance, cost, tech debt, and compliance
• Contribute to event ingestion architecture using Azure Event Hubs, Snowpipe, Fivetran, and Python/TypeScript libraries
• Build and review dbt transformation pipelines
• Define and enforce event contracts and schemas
• Evolve core data models and integrate new sources
• Guide reverse ETL and activation work

Required qualifications

• At least 1 year leading engineers as a team lead or engineering manager
• 7+ years in data engineering or a closely related backend/platform role
• Deep SQL and strong Python, including query optimization and performance tuning on a cloud warehouse
• Production experience with a cloud data warehouse (Snowflake)
• Production experience with a modern transformation framework (dbt)
• Experience with event-driven / streaming ingestion and its failure modes
• Experience on a cloud platform at the infrastructure level (Azure, AWS or GCP)
• Solid data modeling fundamentals
• Experience operating data systems in production with a focus on reliability, observability and maintainability
• Excellent communication in English
• Comfort working directly with non-technical stakeholders

Nice to have

• Experience in a startup or scale-up, ideally as an early member of a data team
• Experience hiring engineers or helping a team expand its scope
• Experience with product analytics tooling (Mixpanel, RudderStack)
• Experience with warehouse-native BI (Netspring/Optimizely Analytics, Omni, Embeddable, or similar)
• Experience building data products for AI or agent consumption: semantic layers, metrics layers, MCP servers, or governed self-service access
• Experience with Terraform, Docker and data governance at scale
• Reverse ETL experience and familiarity with CRM data models (HubSpot, Salesforce) or customer success platforms

Benefits

• 28 vacation days
• Excellent salary
• Pension plan
• Stock participation plan
• Hybrid work (Amsterdam-based)
• International team and environment
• Daily lunch
• Mental health support (OpenUp)
• Social events and team activities

Before you apply

• Recruiter screen (30 minutes, online)
• Hiring Manager interview (1 hour, online)
• System design interview (1 hour, on-site)
• Product interview (1 hour, online)
• Final interviews with Engineering leadership (30 mins, online)

About the company

DataSnipper builds AI solutions that empower audit and finance professionals by making evidence easier to trace and verify. The company serves over 600,000 professionals across 3,000+ organizations in 175 countries.