Staff Analytics Engineer

At Saily, we’re removing the hassle of staying connected while traveling — no roaming fees, no plastic SIM cards, just lightning-fast, secure mobile data in 200+ destinations. Saily has millions of paying customers and hundreds of thousands of travelers browsing through Saily at any given moment.

About this role:

Saily is growing fast, and so is the amount of data behind the product. We’re looking for someone to take ownership of how that data is structured, modeled, and used.

The main challenge is simple: we have raw data, and we need to turn it into clear, reliable models that humans (i.e. Data Analytics team) and AI can actually understand and use.

What you’ll do

• Become a founding member of Saily’s Data team and take the lead in building the entire vertical yourself.
• Own data modeling and schema design across Saily.
• Take raw, unmodelled data and turn it into clean, scalable data models.
• Build a clear semantic layer with consistent entities, relationships, metrics, and definitions.
• Make our data easy to understand and use - both for people and AI.
• Own and evolve our analytics infrastructure and tooling.
• Set standards around data quality, documentation, naming, and governance.
• Work closely with Product, Engineering, Marketing and other teams to understand their data needs and make sure our models reflect how Saily actually works.
• Help shape how Data Analytics operates as Saily grows.

Skills you’ll bring to the table

• 6+ years of experience in Analytics Engineering, Data Engineering, or a similar data-focused engineering role.
• Strong hands-on experience with data modeling and schema design, including dimensional modeling, semantic layers, metrics, entities, and relationships.
• Excellent SQL skills and experience turning raw data into clean, scalable analytical models.
• Experience owning or shaping analytics architecture and making technical decisions while staying hands-on.
• Strong product and business thinking — you understand what the data means and how it can be used, not just how it's stored.
• An entrepreneurial mindset — you look at the product holistically and think beyond the technical side of the problem.
• Confidence working across teams, managing stakeholders, and translating product and business needs into data solutions.
• Experience leading or technically guiding Data Analysts / Analytics Engineers is a plus.

Tools/technologies you’ll use

• Coding Agents
• SQL
• dbt
• BigQuery
• Clickhouse
• Looker
• Internal tooling for analytics
• Airflow