Datadog Platform Expert

This is a remote position.


Datadog Platform Expert

We are seeking a high-level Datadog Expert to audit and optimize our leading client’s primary observability platform. This is not a "user" role; we need an expert capable of re-engineering data flows for maximum efficiency.





Datadog Platform Expertise (Must Have)


Minimum 4+ years of hands-on experience with the Datadog platform in production environments.
Deep expertise across Datadog’s core product suite: Infrastructure Monitoring, APM (Application Performance Monitoring), Log Management, Synthetics, Network Monitoring, and Real User Monitoring (RUM).
Proven experience in Datadog cost optimisation, including data ingestion reduction, licence right-sizing, and metric cardinality management.
Expert-level knowledge of Datadog Agent deployment, configuration, and troubleshooting across bare-metal, VM, and containerised environments (Docker, Kubernetes).
Strong experience with Datadog’s tagging strategy, service catalogue, and custom metrics (DogStatsD, custom checks).
Experience with Datadog API and programmatic management of monitors, dashboards, and SLOs.
Familiarity with Datadog’s pricing model and ability to forecast and optimise costs based on usage patterns.
Cloud Infrastructure (Must Have)

Strong AWS experience (minimum 3+ years), including EC2, ECS/EKS, Lambda, RDS, S3, CloudWatch, and VPC networking.
Experience monitoring AWS cost drivers and correlating infrastructure changes with observability cost impact.
Familiarity with Infrastructure-as-Code (Terraform, CloudFormation) for managing Datadog resources programmatically.
Understanding of Kubernetes monitoring patterns: DaemonSets, sidecar injection, cluster-level metrics, and container log collection.
Service Management and Automation (Must Have)

Experience integrating Datadog with Jira Service Management, including webhook-based alert forwarding and bidirectional status sync.
Knowledge of incident management workflows: escalation policies, runbook automation, and post-incident review processes.
Experience with PagerDuty, OpsGenie, or similar on-call management tools and their integration with Datadog.
Ability to design and implement automated remediation workflows triggered by Datadog alerts.
Data Quality and Analytics (Must Have)

Experience auditing and improving data quality in observability pipelines (metrics, logs, traces).
Strong analytical skills with the ability to identify patterns, anomalies, and data integrity issues in large-scale telemetry data.
Experience designing custom dashboards and reports for engineering leadership, focusing on actionable insights.
Preferred and Bonus Skills

Datadog Fundamentals Certification, Log Management Certification, or APM Certification (highly preferred).
Datadog Cloud SIEM for AWS Fundamentals certification.
Experience with FinOps frameworks and cloud cost management tools (AWS Cost Explorer, Trusted Advisor, CloudHealth, Kubecost).
Experience in financial services or banking environments, particularly with regulatory compliance for data handling and retention.
Familiarity with Thought Machine (core banking platform) or similar modern banking technology stacks.
Experience with AI/ML-driven observability features: anomaly detection, forecasting, Watchdog, and intelligent alerting.
Contributions to or experience with Datadog’s open-source ecosystem (datadog-agent, dd-trace libraries, integrations).
Experience with log parsing, pipeline processing, and log-to-metric conversion strategies in Datadog.







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