Senior Platform Engineer - Data License Plus

AI in this role

databricks

Bloomberg’s Enterprise data business helps our clients get the right data at the right time to drive their operational and research workflows. We build the technological supply chains that source vast amounts of data, model it, link it and deliver it to our clients’ financial services systems while providing accessibility and control along the way. Data Science is driving the demand for more and more data and we’re building the platforms to onboard new datasets quicker, smarter and more transparently than before.
Our flagship product is Data License Plus (DL+), which is a fully managed service that hosts, aggregates, organizes and links all of your Data License data into a unified model designed for immediate use. DL+ can also publish your refreshed licensed content, in a ready-to-use format, directly into your cloud data platform (such as Snowflake, Databricks, AWS RedShift, Google GCP) as it becomes available while maintaining transparency, consistency, quality and control.
The DL+ Infrastructure Platforms team designs, builds, and operates the platforms and deployment pipelines that the wider DL+ engineering organisation depends on. We own the Kubernetes estate, the CI/CD tooling, and the self-service layer that lets application teams ship without raising tickets for every change.
The department is mid-transformation - moving from manual, ticket-based operations toward automated, self-service platforms, and aligning with wider Bloomberg engineering teams. This role is central to that shift, you'll be building and owning the platform layer.
We'll trust you to:

Operate and harden the Kubernetes estate - cluster operations including upgrades, capacity planning, networking, and multi-tenant namespace management across on-premise and hybrid environments.
Own the CI/CD and deployment platform layer - Jenkins, Artifactory, ArgoCD and related tooling - so pipelines are reliable, fast, and extensible without the platform team being a bottleneck on every new service.
Build self-service capability - paved-path templates and tooling that let application teams deploy and operate without manual handoffs.
Implement security and compliance guardrails in the platform - pipeline and supply-chain security (DefectDojo, Keycloak, security scanning), workload identity (SPIFFE/SPIRE), and policy enforcement at admission rather than manual review gates.
Instrument platform observability and SLOs - ensure services shipped through the platform come with baseline dashboards, structured logging, and alerting; contribute to the Quality-of-Service standard the platform is held to.
Contribute to platform networking - ingress/egress, traffic flows, and connectivity, working with the network team where it touches network operations.
Participate in reliability and incident response - root-cause analysis, drift detection, and continuous improvement of platform stability.

You’ll need to have:

Proficiency in at least one systems/scripting language for platform tooling and automation - Python, Go, or Bash.
Hands-on Kubernetes experience at the operational level - cluster upgrades, networking, capacity, and multi-tenancy, not just deploying to a managed cluster.
Strong Linux fundamentals (RHEL especially) in a production environment.
Practical experience owning CI/CD tooling at the platform level (Jenkins, GitLab CI, ArgoCD/Flux, or equivalent) - pipeline templates and shared workflows.
Infrastructure-as-Code and GitOps experience (Helm, Ansible, Terraform, ArgoCD).
A working understanding of platform observability (Prometheus, Grafana, or similar).
The mindset that application teams are your customers - building tools people want to use, and communicating clearly with technical and non-technical colleagues.

We’d love to see:

Experience operating enterprise storage at scale, and database-adjacent platform work.
Kubernetes networking and ingress (Cilium, Calico, ingress controllers, service mesh).
Secrets management and workload identity (SPIFFE/SPIRE, Vault, External Secrets).
Security/compliance exposure - policy-as-code (OPA Gatekeeper / Kyverno), vulnerability scanning, audit and SOC-type controls.
Security - experience with cyber security standards such as CIS Benchmarks and frameworks such as NIST CSF.
Experience in a regulated or audited environment.

If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role. Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.

How we rate this

Senior Platform Engineer - Data License Plus at Bloomberg rates 29 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.