Data Engineer (Infrastructure) - Banking & Finance
Are you a tech-savvy problem-solver looking to propel your career to new heights? Join a company that is recognized as a leading provider of IT solutions in Europe, known for their innovative approach to network management and security. They have built a strong reputation for delivering high-quality products that significantly enhance operational efficiency for organizations of all sizes. The company consistently earns accolades for its cutting-edge technology and exceptional service, solidifying its status as a key player in the IT solutions market.
This could be the perfect opportunity to take your career to the next level. Want to learn more about this opportunity? Feel free to reach out and apply today!
Responsibilities:
• Design and maintain scalable data pipelines that support production trading infrastructure
• Build out and support a new, next-gen Kafka environment
• Work with technologies like Apache Spark, Hadoop, and distributed SQL engines
• Optimize data processing systems to meet the latency, reliability, and throughput demands of trading systems
• Collaborate closely with infrastructure, DevOps, and software engineering teams
• Act as a subject-matter expert for internal users (traders, devs, quants) seeking fast, reliable data access
• Own operational support and continuous improvement of core data platforms
Tech Stack:
• Languages: Python (strongly preferred), Java (bonus)
• Platforms: Kafka (major focus), Hadoop, Apache Spark, Flink
• Infrastructure: Kubernetes, distributed systems, Linux
• Other: Experience with data pipeline monitoring, transformation, and scaling at production level
Required Skills/Qualifications:
• Have 5–10 years’ experience in data engineering
• Have a deep understanding of data movement, streaming, and real-time processing
• Are comfortable working in high-performance environments with large volumes of time-sensitive data
• Can own infrastructure end-to-end and take initiative in optimizing it
• Enjoy collaborating with other engineers, but are also happy to work independently
Location:
• Chicago
• Hybrid, 4 days per week in the office
Benefits:
• Discretionary bonus
• Leading company benefits scheme
Salary:
• Up to $225,000 base salary per annum
Apply tot his job
Apply To this Job
This could be the perfect opportunity to take your career to the next level. Want to learn more about this opportunity? Feel free to reach out and apply today!
Responsibilities:
• Design and maintain scalable data pipelines that support production trading infrastructure
• Build out and support a new, next-gen Kafka environment
• Work with technologies like Apache Spark, Hadoop, and distributed SQL engines
• Optimize data processing systems to meet the latency, reliability, and throughput demands of trading systems
• Collaborate closely with infrastructure, DevOps, and software engineering teams
• Act as a subject-matter expert for internal users (traders, devs, quants) seeking fast, reliable data access
• Own operational support and continuous improvement of core data platforms
Tech Stack:
• Languages: Python (strongly preferred), Java (bonus)
• Platforms: Kafka (major focus), Hadoop, Apache Spark, Flink
• Infrastructure: Kubernetes, distributed systems, Linux
• Other: Experience with data pipeline monitoring, transformation, and scaling at production level
Required Skills/Qualifications:
• Have 5–10 years’ experience in data engineering
• Have a deep understanding of data movement, streaming, and real-time processing
• Are comfortable working in high-performance environments with large volumes of time-sensitive data
• Can own infrastructure end-to-end and take initiative in optimizing it
• Enjoy collaborating with other engineers, but are also happy to work independently
Location:
• Chicago
• Hybrid, 4 days per week in the office
Benefits:
• Discretionary bonus
• Leading company benefits scheme
Salary:
• Up to $225,000 base salary per annum
Apply tot his job
Apply To this Job