Java Data Engineer — Hybrid, SC Cleared (Contract)

Experis Austria; Telford; Hybrid; GBP 120,000 - 140,000; Full time

Job summary

Capgemini is seeking experienced Java Engineers to join an expanding team in a hybrid on-site role in Telford. Two seats are available for engineers with data, API and batch processing expertise working within a DevOps framework.

The contract spans six months, with a total cost to Capgemini of 570 and PAYE via umbrella arrangements. Responsibilities include designing robust data integration solutions, building and operating data pipelines with monitoring and SLAs, and collaborating with product

Qualifications

• Data, API and batch processing experience in a DevOps setting.
• Experience across design, build, and operation of data pipelines.
• Ability to work in Agile ceremonies and collaborate with stakeholders.

Responsibilities

• Design and implement robust, secure and performant data integration solutions (batch and/or near-real-time).
• Build, operate and improve data pipelines (ingestion, transformation, curation) with monitoring, alerting and SLAs.
• Collaborate with product teams and client stakeholders to refine requirements and align decisions to NFRs (cost, performance, security).
• Support incident resolution and ensure service continuity within business hours.
• Share knowledge, mentor colleagues, and contribute to Capgemini's engineering communities of practice.
• Actively participate in Agile ceremonies and work cross-functionally with engineers, analysts and business teams.

Skills

RabbitMQ

Java/Microservices

MongoDB

MySQL

Kubernetes

Grafana/Prometheus

Gitlab

Job Scheduler

Apache Airflow

Power BI

Job description

Capgemini is seeking experienced Java Engineers to join an expanding team in a hybrid on-site role in Telford. Two seats are available for engineers with data, API and batch processing expertise working within a DevOps framework.

The contract spans six months, with a total cost to Capgemini of 570 and PAYE via umbrella arrangements. Responsibilities include designing robust data integration solutions, building and operating data pipelines with monitoring and SLAs, and collaborating with product