Data Engineer

RED Global; Manchester; Hybrid; GBP 60,000 - 90,000; Full time

Job summary

RED Global is seeking an experienced AWS Data Engineering Consultant to design and optimize cloud-based data platforms and ETL/ELT workflows in a hybrid Manchester-area role. You will troubleshoot failures, enhance performance and support AI-ready vector data stores, collaborating with data architects and engineers. Start ASAP, length until EOY with extensions.

The role emphasizes hands-on technical leadership, data modelling and secure, scalable architecture across enterprise pipelines.

Qualifications

• Proven experience building and troubleshooting enterprise-scale data pipelines.
• Strong Python and SQL skills with Spark/PySpark experience.
• Experience with AWS services (S3, Glue, Lambda, Redshift, Athena, EMR, DynamoDB).
• IaC experience using Terraform and/or CloudFormation.
• Understanding of data modelling, data quality, metadata and cloud architecture.

Responsibilities

• Design and optimise AWS data platforms, ingestion pipelines and ETL/ELT workflows.
• Investigate pipeline failures and performance bottlenecks, identifying root causes and solutions.
• Review code, architecture and integration patterns to improve scalability, security and reliability.
• Support vector data stores, metadata management and enterprise data integrations.
• Work closely with Data Architects, Engineers and business stakeholders to deliver technical solutions.

Skills

AWS data platforms

Python & SQL

Spark / PySpark

Troubleshooting distributed processing

Data modelling & metadata

Tools

Terraform

CloudFormation

Job description

RED Global is looking for an experienced AWS Data Engineering Consultant to support cloud-based data platforms.

This is a hands-on role combining technical leadership with the design, troubleshooting and optimisation of enterprise data pipelines. You’ll also support vector data storage and retrieval architectures for AI and analytics use cases.

Role Information:

• Location: Manchester Area
• Working model: Hybrid
• Length: Until EOY + extensions
• Start: ASAP

Key responsibilities:

• Design and optimise AWS data platforms, ingestion pipelines and ETL/ELT workflows.
• Investigate pipeline failures and performance bottlenecks, identifying root causes and solutions.
• Review code, architecture and integration patterns to improve scalability, security and reliability.
• Support vector data stores, metadata management and enterprise data integrations.
• Work closely with Data Architects, Engineers and business stakeholders to deliver technical solutions.

Skills and experience:

• Strong AWS experience across S3, Glue, Lambda, Redshift, Athena, EMR and DynamoDB.
• Proven experience building and troubleshooting enterprise-scale data pipelines.
• Strong Python and SQL skills, with Spark/PySpark experience.
• Experience resolving complex distributed processing issues and reviewing code.
• Infrastructure as Code experience using Terraform and/or CloudFormation.
• A solid understanding of data modelling, data quality, metadata and cloud architecture.