Lead Data Engineer
Summary
Lead Data Engineer who owns and scales TodayTix Group's data platform end-to-end — architecting the Snowflake warehouse and dbt project with CI/CD, enforcing data quality, onboarding new data sources, and leading and growing the engineering team while driving AI adoption.
In this Lead Data Engineer role, you scale and own TodayTix Group’s data platform, enabling product, growth, finance, and CX with a single source of truth and AI tooling. You’ll architect, review, and set technical direction while growing a high-performing team. You’ll interface with cross-functional stakeholders to onboard new data sources and ensure data quality at scale. This is a hands-on leadership role focused on impact, not just modelling, within a fast-moving, ownership-driven environment.
Pay / Benefits- hybrid work environment
- flexible work-from-anywhere days
- generous pension match
- complimentary show tickets
- Employee Assistance Programme
- healthcare cash plan and cycle to work
- Own the data platform end-to-end (dbt project, CI/CD, Snowflake infra)
- Design and lead onboarding of new data sources as the business scales
- Collaborate with product, growth, finance, CX, and portfolio teams to model sources cleanly
- Prioritize a high-demand roadmap and balance reporting, growth analytics, and AI tooling
- Protect data quality with dbt tests, contract-enforced schemas, and CI checks
- Provide technical direction for the warehouse and enforce quality through code reviews
- Lead and develop the team through 1:1s and career development
- Drive AI adoption in team processes and as consumers of the warehouse
- 8+ years in data engineering or software engineering with a data focus
- Led engineers and grown teams (formal or informal)
- Deep SQL and dbt expertise (production dbt projects, tests, contracts)
- Hands-on with Snowflake or other MPP warehouses (Redshift, BigQuery)
- Experience scaling data platforms with onboarding of new data sources
- Full-stack data platform judgement across ingestion, transformation, and consumption
- Strong architecture and code-review skills
- Stakeholder management with product, finance, growth, and CX
- Product/business mindset and measurement of data-driven decisions
- AI fluency and comfort with AI agents as data consumers
- leadership and people management
- cross-functional collaboration
- clear communication
- dbt (models, tests, macros, contracts)
- SQL (deep proficiency)
- Snowflake (and other WDW like Redshift/BigQuery)