Analytics Engineer

TrustedHousesitters is a fast growing, direct-to-consumer marketplace that is redefining pet care and travel. Here at TrustedHousesitters, we’re on a mission to make travel work better for pets, for their people, and for the global community of animal lovers who look after them. We’ve got big plans on becoming the world’s most-loved travel solution for pet people. We’ve built something pretty special: a trusted place where pet owners and sitters connect to keep pets happy at home while their humans explore the world. We’ve already grown into a global community with members in over 140 countries, a product people genuinely love, and a team of more than 100 brilliant humans powering it all. But we’re only just getting started. Our goal? To grow to 1 million members and make TrustedHousesitters the world’s most-loved travel solution for pet people. At the moment, a sit starts every two minutes somewhere on the planet. We want that to be every single minute and we know the only way we’ll get there is with the right people in the right roles. The right people in the right roles will shape our future. So, here’s the big question: Could that be you? We are looking for a highly motivated Analytics Engineer with strong skills working in dbt to join our growing data team. In this role, you will be responsible for transforming raw data into clean, reliable, and well-documented datasets that enable self-serve analytics and advanced data modeling across the business. You’ll sit in our growing Data Platform team, working closely with our Data Manager, Engineers, and business stakeholders to create scalable data pipelines and semantic layers that power reporting, dashboards, MLOps and decision-making. You’ll be working with a modern data stack that is built around Databricks, Segment, Fivetran and dbt. This is a remote, UK-based role, and the hours of work are 37.5 hours per week. The salary range will be £55,000-£65,000 per annum, dependent on experience, plus discretionary bonus and generous equity options. Key Responsibilities:

Data Modeling: Design, build, and maintain robust, tested, and documented data models in dbt to support analytics and business intelligence.

Data Transformation: Optimise the way in which our transformation layer builds to ensure scalability

Collaboration: Partner with data analysts, data scientists, and business stakeholders to understand data needs and translate them into technical solutions.

Governance & Quality: Ensure data accuracy, consistency, and security through validation testing and monitoring tools.

Documentation: Maintain clear documentation for datasets, definitions, and data flows to support data literacy and self-serve analytics.

Tooling & Automation: Improve and automate data workflows, version control, and deployment practices across the analytics stack.

Qualifications:

3+ years of experience in analytics engineering, data engineering, or a related field.

Advanced SQL skills and experience working with modern data warehouses (e.g., Snowflake, BigQuery, Redshift - we use Databricks).

Hands-on experience with advanced modelling techniques in dbt.

A deep understanding of ETL/ELT processes and tools (e.g. Airbyte, Stitch - we use Fivetran).

Experience with data visualisation tools (e.g. Looker, Tableau, Power BI - we use Mode) and BI semantic layers.

Strong understanding of data warehousing principles, dimensional modeling, and analytics best practices.

Git-based workflow familiarity (version control, CI/CD pipelines for data).

Excellent communication skills and ability to work cross-functionally.

Nice to have:

Experience in a cloud environment (e.g. AWS, GCP, Azure).

Exposure to Python for data scripting or orchestration.

Experience designing and implementing data models using Medallion Architecture.

Background in a fast-paced, high-growth environment (e.g., tech, SaaS, ecommerce).

Knowledge of data privacy and governance frameworks.

Experience using Databricks