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Salary
≈ $43k – $79k per year (Estimated)
Location
Hybrid (Tallinn, Estonia)
Seniority
Senior
Employment
Full-Time

First seen by Alion on Oct 29, 2026.

Overview
Company
Impact
Profile match
Bolt is an Estonian mobility super-app that offers a wide range of urban transportation and delivery services across Europe, Africa, Western Asia, and Latin America. Founded in 2013 as Taxify, the platform provides ride-hailing, micromobility rentals such as electric scooters and e-bikes, car-sharing, and food and grocery delivery. Today, the company serves over 150 million customers across more than 45 countries, focusing on providing affordable, fast, and sustainable urban travel solutions.

Job Description

Our whole platform lives and breathes on data. Every step of our product development is powered by robust, scalable data infrastructure 6 and Analytics Engineers are the people who make that possible.

As an Analytics Engineer at Bolt, you work at the intersection of data engineering and product analytics. You own everything between data producers and data consumers: building the pipelines, models, and data products that empower analysts and decision-makers across the organisation. You're a sparring partner to our Product Analysts and a force multiplier for the teams you support.

We operate across four product verticals 6 Ride-Hailing, Delivery (Bolt Food and Bolt Market), Rentals (e-bikes, scooters, and carsharing), and Bolt Business 6 plus two horizontals: Platform and Incentives.

We have multiple open roles across these teams. Once you apply, you'll go through a universal process designed to help you learn more about Analytics Engineering at Bolt 6 and help us find the team that best matches your skills and ambitions.

If you believe great data infrastructure is what separates fast-moving organisations from slow ones, you'll fit right in. Scroll down to find out what it looks like day-to-day!

NB! This is a 12-month fixed-term contract covering a maternity leave.

  • Work closely with product analysts and adjacent stakeholders to prioritize and align analytics engineering roadmaps, ensuring that solutions meet the long-term business needs.
  • Build, expand and maintain reusable data models and metrics in dbt.
  • Set up and manage the architecture, documentation, and key data transformations for in-house and third-party data.
  • Improve the efficiency and impact of product analysts through data products, processes, collaboration and active knowledge-sharing.
  • Develop strategic data products such as segmentation feature store or enable advanced solutions such as interactive metrics trees.
  • Follow system design and architectural best practices and closely collaborate with cross-functional stakeholders to ensure data integrity and efficiency across all processes.

Requirements

  • You hold a Bachelor and/or Master degree in Statistics, Economics, Data Science, Computer Science, Mathematics, Information Management, Business or similar studies.
  • You have significant experience with data modeling, developing analytics architectures for large volumes of data and can demonstrate tangible impact in the area.
  • You are proficient in SQL, Python, Spark, data modelling tools such as dbt and orchestration tools such as Apache Airflow.
  • You possess excellent knowledge of system design and architectural best practices with a focus on reusability, maintainability, reliability, and scalability.
  • You are a strong cross-functional collaborator with a good business sense and excellent communication skills in verbal and written English.

Nice to have

  • Previous exposure to Business Intelligence tools such as Looker or Tableau would be an advantage.

Company offers

  • Accelerate your professional growth with unique career opportunities.
  • Enjoy a rewarding salary and stock options, knowing that as Bolt succeeds, so do you.
  • Take care of your physical and mental health with our wellness perks.
  • Celebrate 5 years at Bolt with a 1-month paid sabbatical to recharge.
  • Connect with colleagues at annual company events and smaller team gatherings.
  • Balance flexibility and in-person collaboration with our hybrid model, including at least 12 monthly in-office days.
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