Data & Analytics Engineer — AI & Dashboards

Galliford Try; Metropolitan Borough of Solihull; On-site; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Be Well programme

Agile Working programme

Pension plan

Private medical scheme

Job summary

Galliford Try is seeking a Data & Development Engineer in Solihull to join the Data, Analytics and Development team within IT. You will handle data lifecycle activities from source connect to data platform, build ETL pipelines, design scalable databases, and develop dashboards for self-service insights.

The role emphasizes data quality, security and collaboration with the wider data practice, including AI applications and standards adopting best practices across the business.

Qualifications

• Strong understanding of database architecture and data modelling.
• Experience with ETL, data pipelines and data integration from multiple sources.
• Experience in reporting, analytics and AI applications is desirable.

Responsibilities

• Data Connection: establish feeds from internal/external sources and design data pipelines into Galliford Try’s data platform.
• Storage and Management: design database architectures for staging and storage, ensure data quality and security.
• Transformation: build ETL pipelines to model data for reporting and analytics.
• Reporting: develop interactive dashboards to enable self-service data access.
• Analytics and AI: apply models and analytics techniques to enhance data value, including ML/AI applications.
• Standards and Best Practice: champion central standards and support wider data practitioners.

Skills

T-SQL

DAX

M Language

Python

Azure data services

Microsoft Fabric

Power BI

Tools

Oracle SQL

Git

Power BI

Azure Data Factory

Job description

Galliford Try is seeking a Data & Development Engineer in Solihull to join the Data, Analytics and Development team within IT. You will handle data lifecycle activities from source connect to data platform, build ETL pipelines, design scalable databases, and develop dashboards for self-service insights.

The role emphasizes data quality, security and collaboration with the wider data practice, including AI applications and standards adopting best practices across the business.