Data Engineer: Pipelines, Spark & Cloud (On-site, UK)

RTX; Astley; On-site; GBP 65,000 - 90,000; Full time

Benefits offered by this job

Contributory pension

Life assurance

Holiday entitlement

Discretionary bonus

Flexible benefits

Enhanced sick pay

Family-friendly policies

37‑hour week

Early finish Friday

Volunteer days

Flexible working

Job summary

Raytheon UK is seeking a Data Engineer for full-time, permanent work on-site at Manchester, Gloucester or London. You will build and maintain data pipelines, transform data for analytics, and work with a cross-functional Agile team.

Applicants should have strong analytics for unstructured data, Python (PySpark, Pandas, PyArrow), Spark and ETL tooling, plus cloud and streaming experience. Clearance (eDV) is required where applicable.

Qualifications

• Strong analytics skills for unstructured datasets.
• Proficiency in Python ecosystem including PySpark, Pandas and PyArrow.
• Experience with distributed data processing (Apache Spark).
• ETL design using Airflow, AWS Step Functions or NiFi.
• Knowledge of cloud services (AWS, Azure or GCP).
• Messaging/streaming systems (Kafka, AWS SQS, etc.).
• SQL and NoSQL databases/storage (HDFS, Iceberg, Elastic, S3).
• Containerisation/orchestration (Docker, Kubernetes, OpenShift).
• Testing frameworks and best practices.

Responsibilities

• Build data pipelines that clean, transform, and aggregate data from disparate sources.
• Collaborate with stakeholders and other engineers.
• Contribute to milestone completion on your project.
• Contribute to continuous improvement within the team.
• Collaborate on technical direction within the team.

Skills

Analytics

Python

Spark

ETL

Cloud platforms

Messaging/Streaming

SQL/NoSQL

Containerisation

Testing

Tools

PySpark

Pandas

PyArrow

Apache Spark

Airflow

AWS Step Functions

NiFi

AWS

Azure

GCP

Kafka

DynamoDB/S3

Docker

Kubernetes

OpenShift

Job description

Raytheon UK is seeking a Data Engineer for full-time, permanent work on-site at Manchester, Gloucester or London. You will build and maintain data pipelines, transform data for analytics, and work with a cross-functional Agile team.

Applicants should have strong analytics for unstructured data, Python (PySpark, Pandas, PyArrow), Spark and ETL tooling, plus cloud and streaming experience. Clearance (eDV) is required where applicable.