Senior Data Observability Engineer
CZE - Central Bohemian - Prague (Five)CompetitiveHybridFull time0 applicants
About this role
Job Description
We aspire to be the premier research-intensive biopharmaceutical company. We're at the forefront of research to deliver innovative health solutions that advance the prevention and treatment of diseases in people and animals. As a Senior Data Observability Engineer in the Central Data & Analytics Office, you will help shape the foundational capabilities that make enterprise data reliable, measurable, and scalable. Embedded in Core Data & Engineering and working with a global team, you will design and operate observability and optimization capabilities used by product and delivery teams across platforms. Your work enables faster detection of issues, better performance and cost visibility, and continuous improvement across data pipelines and products.
Responsibilities
- Build, test, deploy and operate core data observability capabilities.
- Participate in all phases of the software development lifecycle for the data observability solution.
- Define and implement metrics, logs, alerts, and signals to make data workloads observable, reliable, and secure.
- Specify platform requirements, standards, and telemetry for cloud, CI/CD, and runtime environments to ensure reliable, secure, and cost-efficient operation of data products.
- Provide L3 production support and act as an engineering subject matter expert to support adoption and troubleshooting.
- Develop engineering guides, document engineering designs, best practices, and runbooks.
- Work within global Agile/Scrum teams, participate in planning, sprint ceremonies, and cross-functional reviews.
- Evaluate and validate new COTS products features within the CDAO ecosystem.
- Work with COTS product vendors on their solutions enhancements and integration into CDAO ecosystem.
- Define and automate scalable onboarding patterns for new data connection types within the data observability platform.
- Build, maintain and improve Infrastructure-as-Code modules, GitOps flows, and CI/CD pipelines for repeatable, auditable deployments across environments.
- Prepare for operation and deploy serverless components (Lambda, EventBridge, Kinesis) and object/data storage (S3); Glue crawlers and other ETL/metadata components.
- Implement and deploy components for platform health, reliability, and performance monitoring; build dashboards, alerts, and runbooks allowing iterations on platform services SLOs/SLIs.
- Optimize infrastructure costs and performance through rightsizing, autoscaling, savings plans/commitments, and architecture improvements.
Requirements
- Proven experience as an AWS platform/infrastructure engineer supporting data workloads.
- Strong Infrastructure-as-Code and GitOps skills: Terraform, Flux, Helm, GitHub (repos and actions).
- Hands-on experience designing and enforcing IAM roles/policies, VPC/subnet design, security groups, and network ACLs.
- Practical experience with Kubernetes on AWS (including Fargate), container deployments, RBAC, and Helm charts.
- Experience with serverless patterns and services: Lambda, EventBridge, Kinesis.
- Familiarity with S3 and AWS Glue (including Glue crawlers) and how they support data pipelines.
- Experience with infrastructure monitoring and observability (metrics, logs, tracing) and building dashboards/alerts.
- Demonstrated experience optimizing cloud costs and performance at the infrastructure layer.
- Solid skills in Python and SQL for automation, tooling, and supporting data teams.
- Comfortable working in Agile/Scrum environments and collaborating with cross-functional global teams.
Nice to have
- BSc in IT, Engineering, Computer Science, or related field.
- Experience with data observability tooling or frameworks (great advantage).
- Hands-on Apache Airflow experience (deployment, DAG troubleshooting, scaling, metadata understanding).
- Knowledge of Grafana Labs stack (Grafana, Loki, Tempo, Agent) or similar observability ecosystems.
- Experience implementing policy-as-code, security automation, or compliance guardrails.
- Familiarity with SRE practices (SLOs/SLIs, incident response) and platform reliability engineering.