Senior Analytics Engineer

About Us

Perk (formerly TravelPerk) is the intelligent platform for travel and spend management. Built to tackle the time-consuming, manual work that gets in the way of real work, our tools automate everything from travel bookings to expenses, invoice processing, and more. By eliminating this shadow work that wastes hours, erodes morale, and saps innovation, we're on a mission to power real work, with real impact.

We're trusted by more than 12,000 companies worldwide, including Bolt, GoCardless, and Fabletics, and we're tackling the 7 hours of lost productivity per employee each week, a $1.7 trillion problem .

Founded in 2015, Perk has grown into a global company of more than 1,800 people across 12 offices globally, with headquarters in London and Boston. We combine innovation, control, and simplicity to transform how businesses work and how people feel at work.

At Perk, we're driven by our values, like being an owner, delivering a 7-star experience, and working as one team. We value curiosity, purpose, and mindset, not just knowledge, to unlock the power in your potential. Our talent team brings together leading minds from the travel, fintech, and SaaS industries, representing over 70 countries. If you're excited about having a real impact and shaping how millions of people experience work, we'd love you on the team.

Visit www.perk.com to learn more.

Overview

This critical role sits at the intersection of Data Engineering and Data Analytics, focusing on transforming raw data into high-quality, trustworthy, and easily consumable datasets and visualisations for business users. The ideal candidate will possess a strong background in SQL, dbt, data modelling, ETL/ELT principles and experience with modern cloud data platforms.

Core Responsibilities

Develop and Maintain Transformation best practices in ELT Pipelines: Design, develop, and maintain efficient and scalable workflows using tools like dbt to transform raw data loaded into our data warehouse (Snowflake) into clean, ready-to-use data models.

Data Modelling: Implement best-practice data modelling and software engineering techniques to ensure data structures are optimised for performance, accuracy, and ease of use in reporting and analytical applications (e.g. CI/CD, testing, lineage).

Data Quality and Testing: Write comprehensive data quality checks, tests, and monitoring scripts to ensure the accuracy, completeness, and reliability of all transformed data assets. Establish and maintain documentation for all data transformations and models.

Collaboration: Work closely with Data Analysts and business users to understand their reporting needs and optimise data models to support their analytical use cases. Collaborate with Data Engineers on data ingestion strategies and platform optimisation.

Performance Optimisation: Tune and optimise SQL queries and data models to reduce latency and improve the performance of our data warehouse and downstream applications.

Tool Adoption: Champion the adoption of modern data stack tools and practices (e.g. Git, CI/CD).

Build scalable, compelling data visualisations in Looker that can be used by large teams.

Required Qualifications

Experience: Multiple years of experience in a data-focused role (e.g., Analytics Engineer, Data Analyst, BI Developer).

SQL Mastery: Expert-level proficiency in writing and optimising complex SQL queries.

Data Transformation Tooling: Hands-on experience with dbt (Data Build Tool) or similar data transformation frameworks is essential.

Data Warehousing: Experience working with cloud-based data warehouses such as Snowflake, Google BigQuery, or Amazon Redshift.

Data modelling: Solid understanding of data warehousing concepts, ETL/ELT principles, and dimensional modelling techniques.

Version Control: Proficiency with Git for collaborative development and version control.

Familiarity with reporting/ BI tools like Looker.

Preferred Qualifications

Python expertise for automation, integration, and orchestration

Experience with Semantic layers

Experience with orchestration tools like Airflow.

Knowledge of modern software engineering practices applied to data (e.g., modularity, code review, testing).

Our Vision is for a world where TravelPerk serves as the platform for human connection in-real-life (IRL). We take an IRL-first approach to work, where our team works together in-person 3 days a week. As such, this role requires you to be based within commuting distance of our London or Barcelona  hub . We fundamentally believe in the value of meeting in-real-life to improve connectivity, productivity, creativity and ultimately making us a great place to work.

For certain roles, we can help with relocation from anywhere in the world, English is the official language at the office. Please submit your resume in English if you choose to apply. Do not forget to submit an updated portfolio and/or resume.

TravelPerk is a global company with a diverse customer base—and we want to make sure the people behind our product reflect that. We’re an equal opportunity employer, which means you’re welcome at TravelPerk regardless of how you look, where you’re from, or anything else that makes you, well, you.

AI at Perk

AI is embedded in how we work across every function. The tools you'll use day-to-day are AI-enabled so you can move faster and spend more time on the work that matters. In practice, that means using AI to research and prioritise accounts, draft and refine outreach, handle customer interactions more effectively, synthesise information, and cut through shadow work - the invisible tasks that pull people away from the work only they can do - so you can focus on relationships and outcomes.

How We Work

At Perk, we take an IRL-first approach to work, where our team works together in-person 3 days a week. As such, this role requires you to be based within commuting distance of our hubs. We fundamentally believe in the value of meeting in real life to improve conne