Senior Principal - Product Owner - Observability
Bengaluru · Full time · Posted 6D AGO
Business Introduction
GSK remains committed to achieving bold commercial ambitions for the future. By 2031, we aim to deliver £40 billion in annual sales, leveraging our existing strong performance momentum to significantly increase our positive impact on the health of billions of patients globally. Our Ahead Together strategy is centred on early intervention to prevent and alter the course of disease, thereby protecting people and supporting healthcare systems.
Our diverse portfolio consists of vaccines, specialty medicines, and general medicines.
Through continuous innovation and a dedicated focus on scientific and technical excellence, we strive to develop and launch new, groundbreaking treatments that address critical health challenges.
Job Purpose
The Senior Principle Owner – Observability owns GSK's enterprise observability platform (observability.gsk.com) as a product. This is a techno-functional role. It sets the product vision and owns and orders the backlog, and it is hands-on enough to configure BindPlane and OpenTelemetry pipelines, write parsing rules, script ingestion utilities, build Grafana dashboards and debugging issues.
The role leads the platform's back-end migration from self-managed Prometheus/Mimir and Elastic SaaS to Google Cloud Observability. Telemetry collection moves to BindPlane (Google Edition), and Grafana remains the single interface for GSK teams. Beyond the migration, the role turns into managing backlog, licensing & transforming platform with AI capabilities into services that business teams use directly: plain-language questions about service health, early warning on business-critical processes, and clear incident and health summaries.
Success is a platform that teams adopt by choice: onboarding through golden templates rather than tickets, SLOs that reflect what the business needs, and alerting that cuts noise rather than adding to it. The role treats consuming teams as customers, because they can route around a platform that is hard to use. It links platform work to D&T and business outcomes, and makes the cost of deferred technical debt, upgrade and instrumentation work visible.
Key Responsibilities
1. Platform ownership – Run observability.gsk.com as a product with a clear vision, roadmap, SLOs, capacity plan, run-cost model and lifecycle (patching, upgrades, end-of-life). Own and order the backlog, linking each item to platform OKRs and stating the cost of not doing it.
2. Google migration – Deliver the back-end migration from Prometheus/Mimir and Elastic SaaS to Google Cloud Observability (Cloud Logging, Managed Service for Prometheus, Cloud Trace) before the Elastic contract ends in April 2027. Sequence waves by business criticality, run old and new in parallel, and prove parity for core metrics, dashboards, alerts and log searches. Keep the Grafana experience unchanged, and decommission legacy components without loss of coverage or audit history.
3. Reliability – Achieve 99.9% availability for tier-1 platforms. Agree SLOs with service owners, close coverage gaps so reliability is measured rather than inferred, and lead incident response, blameless post-incident reviews and problem management. Replace repeated manual recovery with permanent automated fixes.
4. Telemetry pipelines and data quality – Own how telemetry reaches the platform. Run the OpenTelemetry agent fleet through BindPlane (Google Edition), covering sources, processors, destinations and staged config rollout. Own parsing and normalisation (Grok and regex, structured JSON logging, consistent labels and resource attributes), the Python and OTel utilities that ingest end-user services (EUS) telemetry, synthetic monitoring, and Google Data Fusion feeds for network telemetry. Control ingest cost through sampling, filtering, exclusions, retention and cardinality management.
5. Architecture and scaling – Partner with the Observability/Platform Architect on how the platform scales: BindPlane gateway and collector topology, Google Cloud project, metrics-scope and log-bucket design, log routing, multi-region and hybrid (GCP, Azure, on-premise) coverage, cardinality and retention. Translate business demand into capacity and architecture decisions, and explain the trade-offs to business stakeholders in plain terms.
6. AI-powered observability for business teams – Offer AI in observability as a product that R&D, Manufacturing, Supply and Commercial teams use directly: plain-language questions about service health, proactive early warning, and AI-generated incident and service-health summaries. Build the unified data model across metrics, logs and traces that underpins this and the AI for Tech platform, using BigQuery, BigQuery ML, Vertex AI and Gemini, with governed use of third-party LLMs. Route alerts to ServiceNow ITOM and the AIOps platform, and maintain Grafana plugins for external sources such as ServiceNow and Oracle.
7. Everything as code, secure by default – Manage collector configs, parsers, log sinks, alert policies, dashboards and access in Git through IaC (Terraform Google and Grafana providers, BindPlane config, Ansible) and GitOps; no configuration lives only in a console. Build in SSO, least privilege, project isolation and masking of sensitive data from the start.
8. Observability templates and developer experience – Build reusable OTel instrumentation templates, BindPlane configs, parsers and Grafana dashboard packs so delivery teams onboard and self-serve without tickets. Measure and improve DORA metrics and platform NPS, and provide onboarding, documentation, migration guides and office hours.
9. Leadership – Set standards, review designs and code, and mentor engineers, including partner engineers. Manage vendor and partner relationships (Google, observIQ/BindPlane, Grafana Labs, Elastic through exit, ServiceNow, Red Hat, GitHub, Microsoft), holding partner-delivered work to internal standards. Apply the Platform Architect's reference architectures and raise a case for change rather than diverging locally.
Experience Required:
Experience
• Overall, 15 Years and 12+ years in platform, infrastructure or software engineering, with hands-on platform experience
• 5+ years owning a production platform end-to-end at enterprise scale (5,000+ users), including product ownership of its backlog and roadmap
Observability
• Hands-on Google Cloud Observability in production: Cloud Logging (log router, sinks, buckets, log views, Log Analytics, Logging Query Language), Cloud Monitoring and Managed Service for Prometheus (PromQL, alerting policies, metrics scopes), and Cloud Trace
• Hands-on Prometheus/Mimir and Elastic (Elasticsearch, Logstash, Kibana, ingest pipelines), enough to run the legacy stack and exit it safely
• Grafana in depth: dashboards as code, alerting, data sources, plugins, folders and RBAC
• OpenTelemetry: SDKs, collector, semantic conventions and resource attributes
• Defines SLOs and alerting that cut noise, with evidence of before-and-after impact
Telemetry pipelines and parsing
• BindPlane (Google Edition preferred) or equivalent OTel fleet management: agents, sources, processors, destinations and staged config rollout across large fleets
• Writes and debugs Grok patterns and regex that turn unstructured logs into structured fields (Logstash, Elastic ingest pipelines, BindPlane/OTel processors), and moves teams to structured JSON logging
• Builds Python ingestion utilities for non-standard sources, such as end-user services, using OpenTelemetry
• Applies sampling, filtering, enrichment, PII masking and multi-destination routing, including telemetry shared with a SIEM
• Controls ingest cost through log exclusions, retention, metric cardinality and sample volume
Scripting and programming
• Strong Python (ingestion utilities, OTel SDK, automation) plus Go or PowerShell; comfortable with Bash
• REST APIs and webhooks (Google Cloud, Grafana, BindPlane, ServiceNow, Elastic) for automation and integration
• Reads and writes PromQL, Logging Query Language, BigQuery SQL and KQL/Lucene; reviews YAML, HCL and Helm charts with confidence
Infrastructure as code
• Terraform and Ansible in production estates
• GitOps workflows, with configuration managed in Git rather than consoles
Cloud
• Production experience in GCP, where the observability platform runs
• Production experience in Azure, where much of the observed estate runs
• Kubernetes fundamentals across GKE, AKS or OpenShift
Security
• Identity (Entra ID, SSO, SCIM)
• Secrets management, Google Cloud project isolation and IT/OT data segmentation
• Least privilege and software supply-chain security
Techno-functional
• Works with the Observability/Platform Architect on scaling decisions (BindPlane gateway topology, cardinality, retention, multi-region) and holds a technical position in that discussion
• Turns business requirements into SLOs, backlog items and acceptance criteria, and explains technical trade-offs to non-technical stakeholders
Should have
AI in observability
• Has enabled AI assistance for non-engineers on an observability platform, such as plain-language questions over telemetry (e.g. Gemini over Cloud Logging and BigQuery, surfaced in Grafana or chat), with answers grounded in governed data and traceable to source
• Has built anomaly detection or forecasting (e.g. BigQuery ML, Vertex AI) that alerts business owners in business terms before users notice
AIOps and event correlation
• Hands-on with an AIOps or event-correlation platform (e.g. Neuberg, Moogsoft, BigPanda, ServiceNow ITOM)
• Has built closed-loop auto-remediation with guardrails, human approval gates and audit trails
OpenTelemetry at scale
• Has set instrumentation standards, collectors and pipelines across multiple languages
Regulated delivery
•Has worked under change control in a regulated industry (pharma, healthcare, finance) and can produce audit evidence
Market awareness
• Exposure to SaaS observability platforms such as Datadog, Dynatrace or New Relic, enough to assess them for future platform decisions
Desirable
• Certifications such as Google Professional Cloud DevOps Engineer or Cloud Architect, Azure Solutions Architect Expert, or Grafana or OpenTelemetry certifications
• Product ownership certification or practice (e.g. CSPO, PSPO) applied to an internal platform
• Understanding of AKS and GKE security practices
Skills/Background
• Customer mindset toward consuming teams, who can route around a platform that is hard to use
• Business translation: turns what a lab, plant or commercial system needs into SLOs and backlog priorities
• Automation-first instinct: treats a repeated manual task as a defect, not as work
• Makes technical debt and its cost visible rather than absorbing it silently
• Sound judgement on when AI-generated code and configuration are fit to merge
Skills
Why GSK?
Uniting science, technology and talent to get ahead of disease together.
GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.
People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.
Inclusion at GSK:
As an employer committed to Inclusion, we encourage you to reach out if you need any adjustments during the recruitment process.
Please contact our Recruitment Team at IN.recruitment-adjustments@gsk.com to discuss your needs.
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