Senior Data Analytics Engineer

We're looking for a Senior Data Analytics Engineer to join our passionate and diverse Data Team. Treatwell is an organisation built on data, and we're just getting started. In this role, you'll be instrumental in shaping our future by ensuring our data models and analytical capabilities keep pace with the rapid growth of our business.

As part of the Data Domain Team, you'll take end-to-end ownership of data products that empower analysts, product managers, and business stakeholders with meaningful insights. You'll work closely with teams across the business, translating their needs into reliable, well-structured data assets.

You'll bring strong expertise in SQL, Python, and data model design to deliver the right data in the best format through self-serve and Machine Learning-enabled tools. We work with open-source platforms including DBT, Airbyte, Docker, GitLab, SageMaker, and Airflow. Our services run on AWS, including Redshift, ECS, Lambda, Cloudwatch, S3, EMR, and EC2, alongside third-party tools like Fivetran, Monte Carlo, Looker, JIRA, and Slack.

We're also at an exciting point in our data journey with plans to modernise our data stack and transition to a Lakehouse architecture. This is a great opportunity to help shape the direction of how we store, model, and access data at Treatwell. You will be responsible for:

• Collaborating with your data peers and business teams to understand their needs and build data products that surface performance insights and drive action
• Modelling core data assets using SQL, DBT, Python and LookML
• Supporting the development of Machine Learning models using Python and AWS SageMaker
• Contributing to the strategy and design of data models and the data warehouse
• Supporting the discovery and integration of new data sources (OLTP, APIs, S3)
• Empowering analysts and business users through conversational analytics, self-serve tooling, education, and documentation
• Defining and managing data quality, documentation, observability, and governance of core data models
• Managing data exposures in Looker, ensuring smooth and reliable delivery of data to the business
• Automating repetitive analyses and tasks wherever possible
• Investigating and proposing solutions for data warehouse issues arising from daily query processing and end-user needs
• Fostering a data-driven culture across the organisation