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Randstad Technologies Careers

London / Global

Data Engineer

  • Hybrid

Job Description

Job title: Data engineering specialist

Locations: London One Braham or Birmingham Snowhill or Bristol Assembly (hybrid-3 days onsite)

Start Date: Need candidate who are immediately available to join

Duration: 06 months

IR35: Inside

Job description:

Role Overview

We are seeking an experienced Analytics Engineer to design and build scalable analytical data models that support business intelligence, reporting and commercial analytics.

The role sits within a multidisciplinary data team responsible for delivering trusted analytical data products used across commercial and marketing teams.

The ideal candidate will combine strong analytical thinking with advanced SQL engineering capability, and will have experience designing analytics-ready datasets used by BI tools or semantic layers. This is not a pipeline engineering role; we are looking for someone experienced in building analytical data models that define consistent business metrics and enable self-service analytic s.

Key Responsibilities

Analytical Data Modelling

Design and implement scalable analytical data models in SQL used by BI tools and analytics platforms.

Build datasets that support consistent business metrics, reporting and analysis.

Implement modelling approaches such as star schemas, denormalised analytical tables and reusable metric layers.

Data Analysis & Profiling

Profile complex datasets to understand data structure, quality and business meaning.

Investigate and interpret source data to inform robust analytical modelling decisions.

Translate business questions into well-structured analytical datasets.

SQL Engineering

Develop robust SQL transformations to convert raw source data into trusted analytical assets.

Ensure analytical models are scalable, performant and maintainable within a cloud data warehouse.

Optimise SQL logic for performance and efficient data processing.

Collaboration

Work closely with analysts, visualisation developers, data engineers and business stakeholders.

...

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