Observability Engineer

Crest Data; Ahmedabad District; On-site; INR 2,000,000 - 3,600,000; Full time

Job summary

Crest Data is seeking an Observability Engineer/Consultant to design, implement, and optimize observability solutions across complex environments. You will own the delivery of instrumentation, dashboards, alerts, and SLO frameworks, interfacing with engineering and operations stakeholders.

The role requires hands‑on tool depth, strong scripting ability, and experience across Kubernetes, Docker, and multiple cloud providers. Collaboration and clear technical communication are essential.

Qualifications

• 6+ years of hands‑on experience implementing or consulting on observability solutions in production environments.
• Proficiency with at least one enterprise observability platform (Dynatrace, Datadog, New Relic, Elastic Stack, or Splunk) including agent deployment, data ingestion configuration, and use case development.
• Working knowledge of Metrics, Logs, and Traces and related tooling.
• Experience with OpenTelemetry or vendor‑native tracing agents.
• Familiarity with Kubernetes, Docker, and at least one major cloud provider (AWS/Azure/GCP).
• Ability to read/write scripts or queries in Python, Bash, SPL, DQL, KQL, LogQL, PromQL, or equivalents.
• Strong technical communication skills for documentation and stakeholder discussions.

Responsibilities

• Deploy and configure observability platforms across on‑premises, cloud, and hybrid environments.
• Instrument applications and infrastructure to collect metrics, logs, and traces.
• Design dashboards, alerts, and SLI/SLO frameworks.
• Define standards for log structuring, trace propagation, and metric naming.
• Integrate observability tooling into CI/CD pipelines and data pipelines.
• Produce architecture diagrams, runbooks, and onboarding guides.

Skills

Observability

OpenTelemetry

PromQL

SPL

Kubernetes

Python

Cloud

Tools

Dynatrace

Datadog

New Relic

Elastic/ELK

Splunk

Job description

Crest Data is the global leading provider of Data Analytics, Security, DevOps, Cloud Solutions, Software integrations, Analytics, and security-based technological services. With a clientele that includes several Fortune 500 corporations and some of the innovative Silicon Valley Startups.

Company URL

http://www.crestdata.ai

Experience : 6+ Years

Role Summary

We are hiring an Observability Engineer/Consultant to design, implement, and optimize observability solutions across complex customer or internal environments. You will own the technical delivery of observability use cases— from instrumentation and data pipeline configuration to dashboards, alerting, and SLO frameworks. This role sits at the intersection of platform engineering and consulting, requiring both hands‑on tool depth and the ability to communicate technical decisions clearly to engineering and operations stakeholders.

Key Responsibilities

• Deploy and configure observability platforms (Dynatrace, Datadog, Elastic, Splunk, New Relic, or equivalent) across on‑premises, cloud, and hybrid environments.
• Instrument applications and infrastructure to collect metrics, logs, and distributed traces aligned to business and operational requirements.
• Design and build dashboards, alerting rules, and SLI/SLO frameworks that surface actionable signal rather than noise.
• Define and enforce standards for log structuring, trace propagation, and metric naming conventions across engineering teams.
• Integrate observability tooling into CI/CD pipelines, cloud‑native infrastructure (Kubernetes, Docker), and data pipeline components (e.g., OpenTelemetry Collectors, Cribl, Logstash).
• Conduct observability assessments for customer environments, identify coverage gaps, and deliver implementation roadmaps with clear prioritization.
• Produce technical documentation including architecture diagrams, runbooks, onboarding guides, and platform‑specific configuration standards.

Required Qualifications

• 6+ years of hands‑on experience implementing or consulting on observability solutions in production environments.
• Demonstrable proficiency with at least one enterprise observability platform: Dynatrace, Datadog, New Relic, Elastic Stack (ELK/EFK), or Splunk— including agent deployment, data ingestion configuration, and use case development.
• Working knowledge of all three observability pillars: Metrics (collection, aggregation, PromQL or equivalent), Logs (structured logging, pipeline configuration, query languages), and Traces (distributed tracing, context propagation, APM instrumentation).
• Experience with OpenTelemetry (SDK instrumentation, Collector configuration, OTLP pipelines) or equivalent vendor‑native tracing agents.
• Familiarity with containerized and cloud‑native environments: Kubernetes, Docker, and at least one major cloud provider (AWS, Azure, or GCP). Ability to read and write scripts or queries in at least one of: Python, Bash, SPL, DQL, KQL, LogQL, PromQL, or equivalent.
• Strong technical communication skills— able to produce clear documentation and explain architectural decisions to both engineering teams and non‑technical stakeholders.

Nice‑to‑Have Qualifications

• Platform certifications: Dynatrace Associate or Professional, Datadog Fundamentals, Splunk Core Certified Power User or Splunk Admin, Elastic Certified Engineer, or New Relic Observability Practitioner.
• Experience with log and telemetry pipeline tools: Cribl Stream, Fluentd, Vector, or Kafka‑based architectures.
• Exposure to SIEM platforms (Splunk ES, Palo Alto Cortex XSIAM, Microsoft Sentinel) and understanding of where observability and security telemetry overlap.
• Familiarity with Infrastructure as Code tools (Terraform, Ansible) for managing observability configurations at scale.
• Experience working in a managed service, MSSP, or customer‑facing consulting capacity supporting multi‑tenant or multi‑environment deployments.

What We Offer

• A technically grounded team where engineering decisions are evidence‑based and observability is treated as a first‑class engineering discipline, not an after thought.
• Exposure to diverse technology stacks and customer environments, with real ownership of implementation outcomes.
• Structured career development with support for platform certifications and continued technical specialization.
• Competitive compensation, flexible working arrangements, and a transparent performance review process.