Senior Software Engineer - Data Technologies Compute Platform

Senior Software Engineer - Data Technologies Compute Platform

Location: London

Business Area: Engineering and CTO

Ref #: 10042347

Description & Requirements

Bloomberg is foremost a data company. Data is at the heart of everything we do; we collect it, standardize it, enrich it, validate it, and make it available to our clients. The Data Technologies Infrastructure group is responsible for the platforms that support Bloomberg engineers in getting data into the company from the outside world, and our impact is multiplied by the hundreds of engineers building systems on our platforms.

Data Technologies Pipelines (DTP) is a Kubernetes-based platform specializing in event-driven pipelines that process billions of events per day:

• Our managed connectors allow developers to build event-driven systems out of thousands of simple microservices.
• Our unique traffic mirroring and egress control features allow developers to test their code in a production environment, without affecting downstream systems.
• And our native observability features support developers in monitoring and adapting systems to ever changing incoming data.

We build systems that scale horizontally: operating multi-tenant clusters of hundreds of machines and often pushing storage technologies to their limits. Sometimes this means opting for something more specialized than traditional technology choices (e.g. Cassandra over an RDBMS). Other times it means sticking with something proven but making use of it in creative ways.

What’s in it for you?

• An inclusive and supportive work culture that fosters learning and growth.
• A unique opportunity to work on large scale systems that have a wide impact across the company.
• The opportunity to work on all areas of the stack, from tuning IPVS load balancing strategies, through designing & implementing scalable database schemas & backend APIs, to creating modern, intuitive web UIs.
• The opportunity to influence the future of our platform by designing new system-wide features such as transactional promotion workflows or auto-scalable pipelines with first-class support for different message processing semantics.

Who are you?

• A curious polyglot engineer that enjoys the variety of diving into any and all areas of the stack, and digs deep into details when dealing with specific problems.
• Motivated by delivering value to users and autonomous in leveraging any resources at your disposal to unblock yourself and make progress.
• Relish the challenges of large scale distributed systems, accept that failures are inevitable, and build systems with automatic redundancy and recovery.
• Excited about building on the shoulders of giants by leveraging open source technologies and open standards.
• Happiest when working with a diverse team to design, architect and build a full system rather than working alone on a single component.
• Recognise the importance of automated testing and reproducible operations.

We’ll trust you to:

• Build systems that are simple and reliable on the outside, while dealing with the inherent complexities of distributed systems on the inside.
• Design and take the lead on system enhancements while considering both functional and non-functional requirements.
• Collaborate with your immediate team and the wider engineering organization to achieve the team’s goals.
• Own the entire development lifecycle, from planning to execution to deployment.
• Mentor junior members of the team.

You’ll need to have:

• Proficiency in Golang and Python, with hands-on experience building backend services and RESTful APIs.
• Experience working with Kubernetes for containerization and orchestration.
• Experience designing, building, maintaining, and debugging large scale, distributed systems in production.
• Experience leading, planning, executing, and delivering substantial system-wide projects.
• Knowledge of event driven architectures based on Kafka or similar.
• Knowledge of Linux systems and networking.

We’d love to see:

• Experience building and maintaining platforms for other software engineers.
• Knowledge of deployment automation principles and practices.
• Experience with telemetry technologies such as Prometheus, Grafana, and OpenTelemetry.
• Experience with scalable storage technologies such as Cassandra, and S3.

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