Staff Backend Engineer, Data Systems & Real-Time Analytics

Cint

United Kingdom

On-site

GBP 110,000 - 180,000

Full time

7 days ago
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Benefits offered by this job

Cloud collaboration opportunities
Professional development

Job summary

Cint is seeking a Staff Software Engineer for our Data Solutions & Measurement team. You will design, implement, and scale backend systems powering production research services, with collaboration across Outcomes, Methodology, Recruitment, product, and data science teams.

You will balance 20% leadership of junior engineers with 80% focus on solving complex problems, including migrations to domain‑based architecture and high‑throughput, low‑latency processing.

Qualifications

  • 10+ years of backend software engineering experience.
  • Proficiency in Java; familiarity with Python, Scala, C/C++, and related languages.

Responsibilities

  • Design, implement, scale, and maintain large‑volume data processing systems.
  • Develop event‑driven and API‑based integrations.
  • Contribute to migration toward a domain‑based, scalable architecture.
  • Build software optimized for performance‑sensitive workflows.
  • Investigate technical problems and propose solutions collaboratively.
  • Collaborate with data science and engineering peers.
  • Participate in a collaborative development model with shared ownership.

Skills

Backend engineering
Java
Python
Scala
C/C++
Distributed systems
Event-driven architecture
Performance optimization
Problem solving
Communication

Education

BS in CS/CE or related field

Tools

Docker
SQL/NoSQL databases
Spark
Kafka
Delta Lake
Parquet
PySpark
REST APIs

Job description

Cint is seeking a Staff Software Engineer for our Data Solutions & Measurement team. You will design, implement, and scale backend systems powering production research services, with collaboration across Outcomes, Methodology, Recruitment, product, and data science teams.

You will balance 20% leadership of junior engineers with 80% focus on solving complex problems, including migrations to domain‑based architecture and high‑throughput, low‑latency processing.

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