Data Engineer

Nigel Frank International

Nottingham, United Kingdom

2 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Languages

English

Compensation

£ 80K

Job location

Remote

Nottingham, United Kingdom

Tech stack

API

Artificial Intelligence

Amazon Web Services (AWS)

Data analysis

Data Infrastructure

DevOps

Machine Learning

Operational Data Store

Operational Databases

SQL Databases

Data Streaming

Data Storage Technologies

Operational Systems

Software Version Control

Data Pipelines

Redshift

Job description

An exciting, high-growth technology scale-up is seeking a Data Engineer to help evolve and strengthen its modern data foundations. This organisation builds a global, API-first platform used by major enterprise brands to improve data quality, automate workflows, and enhance the reliability of their marketing and operational data. This is a fantastic opportunity to join a business experiencing rapid expansion, where data is central to product innovation, analytics, machine learning, and AI initiatives. You'll work with modern tooling, collaborate closely with Engineering and DevOps, and help shape a robust, scalable data ecosystem. The Role As a Data Engineer, you will play a key role in building and improving data pipelines, increasing access to platform and event data, and developing reliable, reusable datasets that support analytics and data-driven decision-making. You'll take ownership of evolving the company's AWS-based data infrastructure and contribute directly to high-impact initiatives across analytics, ML, and AI., * Build, maintain and enhance data pipelines from operational systems into analytics platforms

Partner with Engineering & DevOps to support ingestion, replication and platform data flows
Define data storage strategy and manage data in AWS S3
Build analytics-ready datasets in AWS Redshift, using dbt for transformation
Improve data quality, monitoring and documentation across the data stack
Support ML/AI initiatives with clean, well-structured datasets
Ensure data practices align with GDPR, security and compliance standards