Lead Consultant – Observability Engineer – SRE & Datadog Specialist

Ready to build the future with AI
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Inviting applications for the role of Lead Consultant Observability Engineer SRE & Datadog Specialist
We are seeking a highly skilled Observability Engineer with deep expertise in Site Reliability Engineering (SRE) principles and Datadog observability tooling.
This role will be instrumental in driving end-to-end observability maturity optimizing system performance and embedding SRE practices across global platforms.
The role is also expected to actively research prototype and roll out new observability capabilities automation patterns and emerging practices (including agentic and AI-assisted approaches) to continuously evolve the observability ecosystem.
The ideal candidate is methodical detail-oriented and demonstrates strong ownership in building resilient observability solutions that deliver reliability insights enable proactive incident management and ensure operational excellence.
Responsibilities
1)Observability Platform Engineering
Design implement and maintain Datadog-based observability solutions across infrastructure platforms and applications.
Develop and optimize dashboards monitors and alerts to support proactive detection and triage of performance and reliability issues.
Integrate custom telemetry pipelines (metrics logs traces events) aligned with Open Telemetry and platform architecture standards.
Manage instrumentation strategies to ensure accurate and consistent coverage across services.

2. Site Reliability Engineering (SRE) Practices
Apply SRE principles to improve service reliability availability and performance.
Define and track SLIs SLOs and SLAs for critical systems and build feedback loops to continuously enhance service health.
Automate manual operational processes using Python Terraform or CI/CD tooling.
Collaborate with development and platform teams to identify resilience patterns and embed observability by design.
3. Datadog Expertise & Ecosystem Enablement
Serve as the subject matter expert (SME) for Datadog advising on advanced configurations integrations and performance optimization.
Enable distributed tracing APM RUM and synthetics capabilities to support end-to-end visibility.
Implement and maintain Datadog Terraform configurations templates and governance models for enterprise consistency.
Conduct performance tuning and cost optimization for Datadog usage across global environments.
4. Incident & Problem Management
Partner with the Operations and Platform teams to analyze incident patterns and provide root cause insights through observability data.
Lead post-incident reviews and recommend observability-driven improvements to prevent recurrence.
Build automation and correlation mechanisms for real-time alert enrichment and contextual diagnostics.
5. Continuous Improvement R&D and Automation
Proactively identify gaps inefficiencies and manual workflows within the observability ecosystem and design automation-first solutions.
Research prototype and evaluate new observability patterns tools and techniques including AI- and agent-based approaches before scaling them into production.
Build reusable frameworks templates and toolkits to reduce toil and enable self-service adoption across engineering teams.
Continuously improve observability signal quality alert precision and operational efficiency through experimentation and iteration.
Translate learnings from incidents postmortems and usage data into systemic improvements rather than one-off fixes.
Qualifications we seek in you!
Minimum Qualifications
Bachelors degree in Computer Science Information Systems or a related field.
Experience in observability engineering or SRE roles within large-scale distributed systems.
Preferred Qualifications/ Skills
Deep hands-on expertise with Datadog including APM Logs Metrics RUM and Synthetics.
Strong proficiency in:
oInfrastructure as Code (IaC): Terraform
oAutomation: Python Bash or similar scripting languages
oCI/CD pipelines: Jenkins GitLab or GitHub Actions
Experience supporting multi-cloud environments (AWS GCP Azure).
Familiarity with container orchestration (Kubernetes ECS) and service mesh observability.
Understanding of data visualization and analytics for operational reporting.
Exposure to AI-driven observability enhancements or integration with LLM-based insights (a plus).
Certification in Datadog AWS or GCP is advantageous.

Why join Genpact
Lead AI-first transformation Build and scale AI solutions that redefine industries
Make an impact Drive change for global enterprises and solve business challenges that matter
Accelerate your careerGain hands-on experience world-class training mentorship and AI certifications to advance your skills
Grow with the best Learn from top engineers data scientists and AI experts in a dynamic fast-moving workplace
Committed to ethical AI Work in an environment where governance transparency and security are at the core of everything we build
Thrive in a values-driven culture Our courage curiosity and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress
Come join the 140000 coders tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up.
Lets build tomorrow together.

Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race color religion or belief sex age national origin citizenship status marital status military/veteran status genetic information sexual orientation gender identity physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity customer focus and innovation.
Furthermore please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a starter kit paying to apply or purchasing equipment or training.