A senior platform engineer embedded in your team owns the cloud, infrastructure, automation, observability and reliability practices needed to make your systems secure and production-ready.
Design and manage scalable cloud environments with secure networking, compute, storage, access controls and deployment foundations.
AWS, Azure, GCP, Terraform
Build internal platforms, golden paths, reusable templates and developer workflows calibrated to your engineering team’s delivery needs.
Kubernetes, Backstage, Crossplane, Helm
Automated delivery pipelines for applications, services, infrastructure and data workloads with testing, approvals and release controls.
GitHub Actions, GitLab CI, Jenkins, Argo CD
Monitoring, logging, tracing, alerting and SLO practices that help teams detect issues before users are affected.
Datadog, Grafana, Prometheus, OpenTelemetry
Cloud security controls, identity management, secrets handling, policy enforcement and compliance-ready platform guardrails.
Vault, IAM, OPA, Wiz
Version-controlled infrastructure, repeatable provisioning, environment automation and engineering discipline applied to platform operations.
Terraform, Pulumi, Ansible, CloudFormation
To contributing
Dedicated to your team
Minimum engagement
Typical match time
DataTheta team behind them
Production experience
Sprint planning
Platform build
Architecture
Reliability
Ops and handover
Platform Engineer II
3–5 years · Supervised delivery
Best for defined platform tasks, infrastructure tickets, CI/CD improvements and supporting a senior lead. Strong execution focus.
Senior Platform Engineer
5–9 years · Independent ownership
Owns platform work end to end. Makes architecture decisions, improves reliability and raises engineering standards without needing hand-holding.
Principal / Staff Platform Engineer
9+ years · Platform leadership
Sets technical direction for your cloud and platform foundations. Best for major migrations, security-critical infrastructure, or teams needing a technical anchor.
Tell us the stack and the gap
Share the cloud stack, platform context and what they need to own. A 30-minute conversation, no forms.
We propose within 5 days
A named engineer from our bench, with background, experience and a short technical assessment relevant to your stack.
You decide
A technical interview runs your way. If the fit is not right, we rematch at no cost. No commitment until you say yes.
In your team by week two
Structured onboarding, committed platform work, and standups from week two.
See how embedded engineering capability improves pipelines, platforms, quality, and decision speed.
Embedded data engineering support helped unify POS, inventory, and promotion data into reliable pipelines for demand forecasting and planning.
34% forecast accuracy improvement
A governed data platform connected claims, provider, clinical, and member data to support reporting, risk scoring, and operational analytics.
3 weeks to 2 days reporting prep
Event-driven pipelines brought sensor and operational data together to support asset monitoring and early risk detection.
14-day advance failure prediction
Answers to common questions about embedding a senior platform engineer through DataTheta.
We usually propose a suitable platform engineer within 5 working days. After alignment, onboarding is structured so they can contribute meaningfully by week two.
Yes. The engineer is embedded into your team, standups, tools and delivery rhythm. They work as a dedicated contributor, not a disconnected external resource.
Yes. DataTheta matches engineers based on your current cloud, infrastructure, CI/CD, container, observability and security stack. The goal is fast contribution without forcing unnecessary platform changes.
We rematch quickly if the engineer is not the right fit for your technical needs, team culture, or delivery expectations. You should only continue when the match works.
Yes. Engagements can extend into long-term embedded support, platform ownership, or expanded engineering capacity. Many clients start with one engineer and scale once value is proven.
Cloud stack, team size, duration — give us the context. We’ll have a name for you within five working days.
Build reliable pipelines, data platforms, transformations and observability practices that make enterprise data production-ready.
Create trusted models, metrics layers, dashboards and documentation so business teams can make decisions from reliable data.
Develop predictive models, experiments, forecasting systems and machine learning workflows that turn complex data into measurable outcomes.
DataTheta is an enterprise Data, Analytics, and AI consulting company that helps organizations build AI-ready data foundations through Data Engineering, Data Science, Business Intelligence, Data Warehousing, Generative AI, and On-Demand Experts.
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