Data Engineer - Hybrid Manchester, Modern Data Platform

phmg; Manchester; Hybrid; GBP 37,000 - 51,000; Full time

Job summary

PHMG is seeking a Data Engineer in Manchester to design, build and maintain scalable data pipelines. You will join an established Data Engineering team and help modernise our data platform, contributing to data quality and reliability across the organisation.

The role focuses on SQL and Python, cloud data technologies, and data modelling to support reporting and analytics. You will work closely with Reporting, Insights and Data Science teams in a collaborative, agile environment with CI/CD

Qualifications

• Strong SQL skills with complex queries and data transformations.
• Proficient Python for data engineering and automation.
• Experience building data pipelines and ETL/ELT patterns.
• Experience with cloud data platforms and orchestration.
• Knowledge of dimensional data modelling and datasets for reporting.
• Experience with Git-based source control and CI/CD.
• Collaborative, agile mindset and problem-solving ability.

Responsibilities

• Design, build and maintain scalable data pipelines and datasets.
• Develop and improve the Microsoft Fabric data platform.
• Design data warehouse, lakehouse and data integration solutions.
• Apply engineering practices: testing, monitoring, error handling.
• Develop data models to support reporting and analytics.
• Collaborate with cross-functional teams to improve architecture.

Skills

SQL

Python

ETL/ELT

Cloud platforms

Git CI/CD

Data modelling

Agile teams

Tools

Microsoft Fabric

Terraform

Salesforce

Job description

PHMG is seeking a Data Engineer in Manchester to design, build and maintain scalable data pipelines. You will join an established Data Engineering team and help modernise our data platform, contributing to data quality and reliability across the organisation.

The role focuses on SQL and Python, cloud data technologies, and data modelling to support reporting and analytics. You will work closely with Reporting, Insights and Data Science teams in a collaborative, agile environment with CI/CD