Databricks SME & AWS Data Engineer

Experis; Northampton; Hybrid; GBP 80,000 - 100,000; Full time

Job summary

A leading technology recruitment agency is seeking a Databricks SME and AWS Data Engineer for a hybrid role in Northampton, UK. The role involves migrating data systems and developing Proof of Concepts (PoCs) for fraud detection using Databricks and AWS. Ideal candidates will have strong AWS Data Engineering expertise, proficiency in Kafka, and solid programming skills in Python. The position requires collaboration with cross-functional teams to deliver high-quality solutions.

Qualifications

• Strong AWS Data Engineering expertise required.
• Proficiency in Kafka and Databricks essential.
• Solid programming skills in Python and PySpark needed.
• Experience with CI/CD tools like Jenkins or GitHub Actions required.
• Familiarity with cloud-native development and secure coding standards.

Responsibilities

• Collaborate with teams to architect and deliver PoCs for fraud detection.
• Lead ETL & data engineering work on AWS.
• Ensure integration of Databricks into the pipeline.
• Participate in weekly calls to demonstrate progress.

Skills

AWS Data Engineering expertise

Kafka for real‑time data streaming

Databricks for data processing and analytics

Programming skills in Python

Experience with CI/CD tools

Knowledge of secure coding standards

Testing frameworks like PyTest

Job description

Databricks SME and AWS Data Engineer

Location: UK - Northampton (Hybrid)

Duration: 6 months

UMBRELLA ONLY

Project Objective

A key initiative involves migrating from Aerospike to Postgres and leveraging Databricks for back‑testing fraud detection models. This role will contribute to the development and integration of Proof of Concepts (PoCs) from the detection backlog.

Key Responsibilities

• Collaborate with cross‑functional teams to architect, design, develop and deliver PoCs related to fraud detection.
• Lead the ETL & Data manipulation/engineering work on AWS.
• Integrate Databricks‑based back‑testing into the fraud detection pipeline.
• Work closely with architects and other developers to ensure seamless integration with existing systems.
• Participate in weekly stand‑up calls to demonstrate progress and align on deliverables.
• Take ownership of tasks from the backlog, ensuring timely and high‑quality delivery.

Required Skills & Experience

• Strong AWS Data Engineering expertise.
• Proficiency in Kafka for real‑time data streaming and integration.
• Proficiency with Databricks for data processing and analytics.
• Working knowledge of NodeJS would be an added advantage.
• Solid programming skills in Python, PySpark, Spark.
• Candidate must be adept at working with large‑scale datasets, S3, Python, and data cataloguing tools. Familiarity with data engineering best practices is essential.
• Performance and Code Quality – candidate should demonstrate a strong commitment to building high‑performance, scalable, and resilient distributed systems, with an emphasis on clean, maintainable, and testable code.
• CI/CD Proficiency – Hands‑on experience with CI/CD pipelines and tools (e.g., Jenkins, GitHub Actions, GitLab CI, etc.) for automated build, test, and deployment processes.
• Secure Development Practices – Awareness of secure coding standards, data protection principles, and experience working in regulated environments (especially relevant for fraud detection and financial services).
• Testing Rigor – Strong understanding of unit testing, integration testing, and test automation frameworks (e.g., PyTest, etc.) to ensure code quality and reliability.
• Familiarity with cloud‑native development and CI/CD practices.
• Agile mindset with a proactive, developer‑driven approach to problem‑solving.

Ideal Candidate Profile

• A hands‑on architect & developer with a strong sense of ownership and accountability.
• Comfortable working in a collaborative, fast‑paced environment.
• Able to pick up tasks independently, contribute to design discussions, and deliver integrated solutions.
• Strong communication skills to engage with both technical and non‑technical stakeholders.

All profiles will be reviewed against the required skills and experience. Due to the high number of applications we will only be able to respond to successful applicants in the first instance. We thank you for your interest and the time taken to apply.