Full-Stack Data Engineer for Scalable AI Pipelines

Catalyst; North East; On-site; GBP 55,000 - 75,000; Full time

Job summary

Catalyst in Newcastle upon Tyne is recruiting a Data Engineer to join their rapid expansion in full-stack data products. You will design and build data pipelines, APIs, and cloud-based platforms powering analytics and AI-driven solutions.

The role requires strong Python and SQL, experience with data pipelines, and familiarity with Spark/Databricks, cloud platforms, and modern DevOps practices. This is a hands-on, collaborative role in a fast-growing team.

Qualifications

• Degree with 2:1 or 1st in Computing Science or related field.
• Demonstrable experience as a Data Engineer.
• Experience in Financial Services sector is advantageous.

Responsibilities

• Software Design: Develop and maintain production-grade applications and APIs.
• Application Build: Develop reusable, well-tested code following engineering best practices.
• Architecture: Participate in architecture and technical design discussions.
• Testing: Write automated unit, integration, and end-to-end tests.
• Data Pipeline Development: Design and develop data pipelines to import data from internal and external sources and integrate into data platforms.
• Maintenance & Data Reliability: Ensure systems are well-maintained and data quality is high.
• Continuous Improvement & Collaboration: Collaborate with stakeholders to improve data accessibility and usability.
• Cloud infrastructure: Deploy cloud-native solutions using Infrastructure as Code and contribute to cloud architecture.

Skills

Python

SQL

Data pipelines

Spark

Databricks

Cloud platforms

Airflow

Terraform

Kubernetes

Distributed systems

Data reliability

Education

2:1 or 1st in Computing Science/Math/Physics

Job description

Catalyst in Newcastle upon Tyne is recruiting a Data Engineer to join their rapid expansion in full-stack data products. You will design and build data pipelines, APIs, and cloud-based platforms powering analytics and AI-driven solutions.

The role requires strong Python and SQL, experience with data pipelines, and familiarity with Spark/Databricks, cloud platforms, and modern DevOps practices. This is a hands-on, collaborative role in a fast-growing team.