Senior Data Engineer
Indexed description
About Meili
Meili builds technology that enables car rental companies to integrate and partner directly with airlines and travel brands, delivering a friction free traveller experience.
Founded by a team with extensive travel tech experience, we’ve already partnered with 25+ global brands including LATAM, SAS, Lufthansa, Air Canada, Accor Hotels, and FREENOW, and we’re committed to rewriting the rules of ancillary distribution.
You’ll love it here if...
- You want hands-on ownership and the opportunity to understand our data from end to end.
- You thrive in a small team where your ideas and decisions have a visible impact.
- You’re excited to shape how a platform evolves - not simply implement someone else’s design.
- Design, build and maintain the data pipelines that feed our warehouse, including ingestion from partner systems and third-party sources, each with its own quirks and reliability profile.
- Own and extend our modelled analytics layer in Snowflake, turning raw source data into well-documented, well-tested tables that the business can query directly.
- Build data quality and observability into the platform: tests, freshness checks, alerting and lineage, so we find out about a broken feed before a partner does.
- Model the metrics the business runs on, so that a number means the same thing wherever it appears.
- Partner directly with commercial, partnerships and product colleagues to understand what they actually need, and translate vague questions into durable data models rather than one-off queries.
- Set engineering standards for the data team - version control, code review, CI, environments, documentation - and raise the bar for how we work.
- Mentor, coach and train others, while acting as a technical sounding board across the team.
- Substantial building production data pipelines and warehouse models, with clear ownership of systems others depended on.
- Strong, fluent SQL - window functions, incremental logic, query tuning - and solid experience with a cloud warehouse. Snowflake specifically is a real advantage.
- Confident Python for data engineering: ingestion, transformation, testing.
- Dimensional and event-based modelling instincts: you can look at a messy data source and design something sane on top of it.
- Software engineering discipline applied to data - Git, code review, CI/CD and testing.
- Experience with warehouse cost management and query optimisation at scale.
- The communication skills to work with non-technical stakeholders, push back constructively, and create documentation that a colleague can pick up and build on.
- DBT - hands-on experience building and maintaining a modelled transformation layer.
- AWS - comfortable working across the services a data platform actually runs on.
- Terraform - you manage infrastructure as code rather than by hand.
- Travel, airline, OTA, e-commerce or marketplace data experience - especially anything involving bookings, funnels or commission structures.
- Experience with multi-currency data and FX conversion in a reporting context.
- Streaming or near-real-time ingestion.
- BI tooling experience - Metabase, Looker, Power BI or similar - and an eye for making a metrics layer genuinely self-serve
- Generous and flexible annual leave allowance
- Health Insurance
- Paid Family Leave
- Hybrid Working
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