Bitrock is a high-end consulting and system integration company,

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strongly committed to offering cutting-edge and innovative solutions . Our tailored consulting services enable our clients to preserve the value of legacy investments while migrating to more efficient systems and infrastructure. We take a holistic approach to technology: we consider each system in its totality, as a set of interconnected elements that work together to meet business needs.

We thrive on overcoming challenges to help our clients reach their goals, by supporting them in the following areas: Data, AI & ML Engineering; Back-end Engineering, Platform Engineering, Front-end Engineering, Product Design & UX Engineering, Mobile App Development, Quality Assurance, FinOps, GovernanceThe effectiveness our solutions also stems from

partnerships

with key technology vendors, like HashiCorp, Confluent, Lightbend, Databricks, and Meterian.

Who we are looking for
We're looking for a

Datadog & Observability Specialist Freelance

to own the end-to-end rollout of a primary observability platform for a multi-region, multi-tenant environment on Azure Kubernetes.

You will lead the migration from a mature but fragmented self-hosted stack (Prometheus/Thanos, Grafana, ELK, AppDynamics) to Datadog. The project is past the proof-of-concept phase: the agent is deployed via Helmfile, a Terraform repository for Datadog resources is bootstrapped, and a tagging taxonomy is agreed upon. We need a genuine Datadog expert who knows the platform's intricacies and sharp edges to drive this rollout to completion and leave behind an autonomous, self-service platform for our client's engineering teams.

What You'll Do

Rollout and agent configuration





— Take the agent from a handful of QA environments to every cluster and tier, as code in Helm/Helmfile, including host-based instrumentation on the legacy Tomcat and httpd VMs.

Tagging and service ownership

— Enforce Unified Service Tagging and our internal taxonomy across agent, chart and application CD sources, and populate the Software Catalog with real team ownership.

Everything as code

— Own the Terraform estate (DataDog/datadog provider) for monitors, dashboards, SLOs, log indexes and RBAC, wired into Azure DevOps pipelines with remote state.

Monitoring, alerting, incident routing

— Design actionable P1–P4 monitor tiers and SLOs, route them through On-Call and Microsoft Teams, and run the dual-run and cutover from Prometheus.

Integrations

— Connect Azure, Kubernetes, Kafka/Confluent with Data Streams Monitoring, the databases, the JVM/Node/.NET runtimes, RUM, and the OpenTelemetry and Splunk HEC pipelines.

Cost governance

— Control spend through log index and retention strategy, exclusion filters, metric cardinality limits and per-team usage attribution.

Security and access

— Design RBAC and Restricted Datasets, and keep log scrubbing, PII redaction and SQL obfuscation a day-one constraint on regulated data.

Enablement

— Leave behind runbooks, naming conventions and onboarding docs, and run workshops so application teams and partner vendors can operate the platform themselves.

Requirements

Deep,



demonstrable Datadog expertise

— at least one large multi-team, multi-environment rollout personally driven, not just product usage. You know the sharp edges (Terraform provider gaps, API limits around restriction policies, index ordering, cardinality billing traps) and can talk about them concretely.

Strong command across

APM, Logs, Infrastructure, RUM, Database Monitoring, Data Streams Monitoring, SLOs, Software Catalog, On-Call, Watchdog .

Terraform

at professional level, specifically the Datadog provider — module design, remote state, CI/CD integration.

Kubernetes

in production, ideally

AKS , with Helm and Helmfile.

OpenTelemetry

— collector configuration, processors, filters, exporters, and a clear view of where OTel ends and vendor instrumentation begins.

Instrumentation across a mixed estate: JVM (Spring Boot and legacy Tomcat/Java EE), Node.js, .NET.

Azure

fundamentals and

Azure DevOps

pipelines.

Migration experience from Prometheus/Grafana, ELK/Elastic APM, AppDynamics, Dynatrace or New Relic — including the political part, not just the technical part.

Fluent English, and the ability to write a design document other engineers actually read.

Nice to have

Kafka / Confluent Cloud operations.

Splunk, particularly HEC ingestion patterns.

Regulated-data environments (GDPR and equivalents).

Working alongside multiple system integrators on a shared platform. xlwpduy

FinOps or observability cost optimization with real numbers attached.

Duration:

1 year

Start:

September

Recruitment process
Our recruitment process has 3 stages:

First discovery short interview with our HR team

Technical interview with our Team Leaders

Final interview with our Client

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📌 Senior Datadog Consultant - Freelance (Roma)
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