Senior Datadog Consultant
Pubblicato il 13-09-2026 - Bitrock in Trentino-Alto Adige
Who we are
Bitrock is a high-end consulting and system integration company, 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 a