Vetted Datadog Professionals

Paul Liu

Screened

Senior Software Engineer specializing in cloud-native backend and web/mobile apps

Seattle, WA8y exp

“Backend engineer with Tesla experience building Python-based, serverless microservices for a supply chain portal, including a MongoDB-backed tracking/logging system and a reconciler Lambda to manage retries and failures. Has hands-on Kubernetes (EKS) and GitOps (Argo CD) experience, plus real-time Kafka pipelines for fleet/IoT telemetry and proxy-based migrations from monolith systems to AWS databases.”

“Meta engineer focused on reliability/operations tooling who built a unified real-time health dashboard and scalable telemetry pipelines (AWS + Datadog) for thousands of devices. Also shipped an internal LLM-powered knowledge assistant using RAG over wikis/runbooks/logs with strong guardrails and a rigorous eval loop that drove measurable accuracy improvements via automated doc ingestion and embedding updates.”

“Technical lead who shipped a production GPT-4-powered customer support agent for Square, serving a large fintech customer base through a React chat interface with tool-using orchestration, guardrails, and live handoff paths. Brings strong real-world experience in agent reliability, evaluation, observability, and workflow orchestration using Temporal, Sidekiq, Pinecone, Datadog, and Snowflake.”

“AppSec/customer security specialist with Atlassian enterprise cloud migration experience, advising on SSO and API token hardening and driving adoption through phased rollouts. Implemented Snyk (SCA) and SonarQube (SAST) in Bitbucket Pipelines with Jira-based vuln workflows, cutting critical vuln MTTR from 30 to 7 days for financial services customers. Strong in SSO troubleshooting (Okta/SAML) and secure AWS/EKS-based agent integrations with secrets management and Datadog observability.”

Jordan Lineberry

Screened

Senior Full-Stack Engineer specializing in Healthcare SaaS and supply chain systems

New York, NY11y exp

“Backend engineer with healthcare platform experience at Thirty Madison, combining Django for secure, data-heavy core services with FastAPI async microservices for real-time patient monitoring. Led Kubernetes migration with Istio service mesh, autoscaling (HPA), and stateful storage patterns, and implemented GitOps CI/CD using ArgoCD. Also built real-time Kafka streaming pipelines with reliability patterns like idempotent producers and offset management.”

Tejaswini Manjunatha

Screened

Mid-level Reliability Engineer specializing in incident response and LLM-driven support automation

Palo Alto, USA4y exp

“Customer Success Services / Support professional working on Palantir Foundry who productionizes customer integrations (secure OAuth2, scheduled pipelines) and builds LLM-driven support automation (runbook matching) with monitoring and evaluation suites. Also leads developer workshops/demos on Foundry packaging/installation workflows, using live debugging techniques to make concepts concrete.”

“Backend/data engineer with Optum healthcare claims domain experience building high-reliability Python microservices (FastAPI/Kafka/Postgres) and AWS data platforms (EKS, Glue, Redshift). Demonstrated strong production ownership: fixed duplicate Kafka processing via transactional outbox/idempotency, scaled to millions of daily events, and delivered major SQL performance gains (40+ min to <5 min, ~60% CPU reduction). Seeking remote-only work; targets $130k base.”

“Backend/data engineer who has owned production Python APIs and high-throughput async workflows on AWS (FastAPI, Docker, ECS/EKS/Lambda) with mature reliability practices like idempotency, bounded retries, circuit breakers, and strong observability. Also built AWS Glue ETL into an S3/Redshift lakehouse and modernized legacy batch systems via parallel-run parity testing and feature-flagged migrations, including a SQL tuning win cutting a multi-minute query to under 10 seconds.”

greg farhadian

Screened

Senior Software Engineer specializing in cloud data platforms and Java microservices

Remote4y exp

“Backend/data engineer with experience building Kafka-driven real-time pipelines that support ML code deployment and downstream integrations. Currently migrating high-throughput mainframe (COBOL/assembly) processing to Java, using Spark/Databricks to preserve performance and employing rigorous A/B testing across dev/pre-prod/prod with years of historical data.”

Sandeep Rohilla

Screened

Principal Platform Engineer specializing in AI-driven document automation

San Francisco, CA20y exp

“Backend engineer who built an event-driven, multi-service resume review system integrating AI/ML workflows. Demonstrated strong performance engineering (e.g., composite indexing dropping latency from ~600ms to ~35ms and major P95 gains) and high-throughput pipeline optimization via caching, batching, and worker concurrency tuning, with multi-tenant isolation implemented across DB and Redis.”

“Senior software engineer candidate who uses AI and multi-agent workflows thoughtfully to speed up development while preserving engineering rigor for production-critical decisions. Stands out for a clear risk-based framework: leveraging agents for boilerplate, refactoring, testing, and debugging, while relying on fundamentals, metrics, and human review for system design and scalability.”