Data Engineer: Analytics

📋 Description

• Design and build the ingestion, transformation, and modelling layers that client reporting depends
• Own data models end to end: grain, keys, relationships, history, and testing, with the reasoning
• Profile, clean, and reconcile source data before it reaches the reporting layer.
• Build the analytics layer that answers the client's questions, and interpret what the results
• Present designs, findings, and recommendations directly to client stakeholders, including
• Excellent communication and presentation skills

🎯 Requirements

• Minimum 3 years building and maintaining production data pipelines that other teams relied on.
• Certification required: a current cloud certification within the data, analytics, or machine
• Snowflake SnowPro Core, production Snowflake experience, and machine learning deployed to
• Advanced SQL: window functions, CTEs, set logic and aggregation at the correct grain, with the
• Relational database and modelling depth: normalisation, grain, key relationships, slowly changing
• dbt in a production setting: incremental models, snapshots, tests, and a project structure you

🎁 Benefits

• The opportunity to work with the leading global OEMs and their technologies.
• Ongoing professional development, with certifications supported and funded.
• Career growth within a rapidly expanding technology consulting firm.