Tech Lead Data Engineer

Role overview A senior, hands-on technical leadership role within a small, fully remote Data Analytics and BI team that powers analytics for a global hospitality software platform. The position blends Data Architect and Tech Lead responsibilities, owning modelling and warehouse design while guiding a team of Analytical Engineers across Snowflake, dbt, Matillion, and Sigma.

Responsibilities - Set the technical direction for the cloud data platform on Snowflake, including logical and physical data modelling across data products and marts using dimensional patterns such as star schemas, slowly changing dimensions, and conformed dimensions, captured through Architecture Decision Records - Lead end-to-end design and execution of data pipelines covering ingestion, API integrations, custom connectors, ELT/ETL, and orchestration - Strengthen DataOps and CI/CD practices by embedding data-specific discipline into existing Git, CI/CD, and Jira workflows, including automated dbt testing on pull requests, environment isolation, and credential management - Build out governance and observability by evaluating and implementing data catalogue and observability tooling for lineage, freshness, completeness, and failure alerting - Continuously tune Snowflake query performance, clustering, and warehouse sizing to optimise execution time and compute spend - Mentor Analytical Engineers through architectural guidance, design reviews, and constructive challenge inside an Agile planning framework - Modernise the stack and evolve the architecture over time

Requirements - Proven track record as a senior data engineer, data architect, or tech lead operating in cloud data environments - Deep, hands-on experience with Snowflake and dimensional modelling patterns - Strong software engineering discipline applied to data pipelines, including CI/CD and DataOps practices - Experience leading or mentoring data engineers and collaborating with engineering, infrastructure, ML, and business stakeholders - Familiarity with dbt, Matillion, and Sigma or comparable modern data stack tooling

Nice to have - Background designing semantic layers and access patterns that make data ready for AI agents and automated workflows - Experience building out MLOps workflows - Exposure to data catalogue and observability tool selection and rollout - Comfort working across multiple time zones in a remote-first setup

Benefits and work setup - Fully remote role with flexibility to work from anywhere - PTO aligned with local labour requirements - Fully paid parental leave - Country-of-residency-based home office stipend - Access to internal learning programmes and professional development, including manager training and upskilling opportunities