Analytics Engineer

Job title:

Analytics Engineer.

Employment type:

Full time.

Location:

Uxbridge with flexibility to work from home.

The Data Engineering team has recently undergone a technology transformation, migrating from a legacy data warehouse to a brand‑new platform built on Snowflake, dbt, Argo Workflows and Kafka. We are looking for an Analytics Engineer to build and maintain scalable data pipelines that serve our analytics applications for Data Science, Machine Learning and Business Intelligence teams.

• Design and implement robust data models (e.g., star schema, snowflake schema, data vault).
• Develop and maintain dimensional data models to support BI and reporting requirements.
• Develop and implement analytics solutions to track key performance metrics.
• Design and build data pipelines to collect, process, and store large volumes of structured and unstructured data from various sources.
• Develop and maintain data quality checks and validation processes.
• Automate reports, dashboards, and data visualisations to communicate insights and trends effectively to stakeholders.
• Build and maintain tooling and frameworks to automate data pipelines for experimentation and machine‑learning modelling.
• Develop and maintain a deep understanding of product domains to ensure relevant events are produced and new entities and processes are integrated downstream in the Snowflake data platform model.
• Monitor and troubleshoot data pipeline issues and provide timely resolution.
• Collaborate with product managers, data scientists, product analysts and software engineers to identify analytical requirements.

• Bachelor's degree in computer science, engineering, mathematics or a related field.
• 3+ years experience in data/analytics engineering focused on building data pipelines.
• Proficiency in SQL and experience with Python or Java.
• Experience with modern cloud data warehouse platforms such as Snowflake, Big Query, Redshift or similar.
• Experience with cloud‑based data platforms, particularly AWS or GCP.
• Experience with data warehousing, data modelling and ETL development.
• Strong analytical and communication skills and an understanding of how product performance drives commercial goals.
• Hands‑on experience with data visualisation tools such as Tableau, Looker, Streamlit or Power BI.
• Strong problem‑solving skills and attention to detail.

• Previous experience in similar analytics engineering roles focused on product analytics and data modelling.
• Experience working with distributed event stores and stream‑processing platforms such as Kafka or Kinesis.
• Experience with batch processing frameworks such as dbt, Argo Workflows or Apache Airflow.
• Familiarity with Docker, Kubernetes and Amazon EKS.
• Familiarity with continuous integration using Git Hub Actions.
• Familiarity with test‑driven development and XP practices.

• Competitive salary and excellent benefits.

We are an equal‑opportunity employer and strive to create a fair and inclusive environment where every employee can thrive and bring their whole selves to work. We encourage diverse perspectives and are committed to supporting the growth and success of all team members.