Data Analytics Engineer

About the role

The Data Analytics Engineer turns raw data into reliable datasets that teams can use to make decisions. Working with data engineers, analysts and business stakeholders, you will define metrics, build reusable data models and make data easier to find, understand and use. You will own the analytics transformation layer, from gathering requirements and designing models through testing, deployment and ongoing maintenance.

Key responsibilities

• Design, build and maintain SQL-based data models in the cloud data warehouse to support reporting, self-service analytics and business analysis.
• Translate business requirements into reusable datasets and work with stakeholders to define consistent KPIs across reports and dashboards.
• Build and maintain automated data tests and monitoring; investigate data quality issues, trace them to their source and coordinate fixes with the responsible teams.
• Document data models, metric definitions and data lineage so users know where data comes from and how to use it.
• Improve query and transformation performance while managing warehouse compute costs.
• Apply software engineering practices to analytics workflows, including version control, code reviews and automated deployments.

Required profile

• Professional experience in analytics engineering, data engineering, BI engineering or a related role, with hands-on ownership of production data models or pipelines.
• Ability to translate business questions into data requirements and explain modelling decisions to technical and non-technical stakeholders.
• Professional proficiency in English, written and spoken.

Required skills

• Advanced SQL, including complex joins, window functions and query optimisation.
• Hands-on experience with a cloud data warehouse (Snowflake, BigQuery, Redshift or Databricks SQL) and a transformation framework such as dbt.
• Git, code reviews, automated data testing and deployment workflows.
• Preferred: Python, Airflow or Dagster, BI tools such as Looker, Power BI or Tableau, and familiarity with data observability, data catalogs or governance practices.