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Vetted Apache Hadoop Professionals

Pre-screened and vetted.

Apache HadoopPythonDockerSQLApache SparkAWS
AW

Aaron Williams

Senior Full-Stack Engineer specializing in microservices, data pipelines, and cloud platforms

Remote14y exp
MetaUniversity of Chicago
PythonDjangoFastAPIGoFlaskReact+77
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JC

Jacob Chen

Staff Software Engineer specializing in cloud-native healthcare and payments platforms

Remote14y exp
AmazonUniversity of Texas at Dallas
PythonGoJavaKotlinTypeScriptJavaScript+230
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JG

Jian Guo

Screened

Executive Data & AI Leader specializing in enterprise data platforms and analytics

NYC, NY25y exp
Bank of ChinaNYU

“Early-stage founder building a service business targeting small clinics, already with one client. Identified the opportunity by helping a family member and then validating needs through direct client conversations; uses AI (including AI agents) for content generation and plans deeper workflow automation to scale cost-effectively.”

AnalyticsCloud ComputingCost OptimizationData AnalyticsData EngineeringData Governance+120
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BG

Brian Gomez

Screened

Senior Machine Learning Engineer specializing in AI/ML, NLP, and computer vision

United States12y exp
McKinsey & CompanyCornell University

“McKinsey & Company ML/NLP practitioner who builds production-grade AI systems across sectors (notably healthcare and finance), including RAG/LLM solutions, entity resolution pipelines, and embedding-powered search with vector databases. Demonstrated measurable impact (40% reduction in data duplication) and strong MLOps/data workflow practices (Airflow, MLflow, Spark, AWS/GCP, Prometheus, CI/CD).”

A/B TestingAnomaly DetectionApache AirflowApache HadoopApache KafkaApache Spark+149
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SY

Sri Yogesh Dorbala

Screened

Engineering Manager / Tech Lead specializing in large-scale distributed systems

Seattle, WA8y exp
DoorDashPurdue University

“Software engineer focused on personalization and data/ML infrastructure who built a GenAI/LLM-driven carousel ranking system end-to-end, delivering a reported 6–7% order-rate lift. Also designed large-scale personalization ETL (15PB for ~100M users) and created a custom Airflow operator to integrate with Databricks under enterprise version constraints, with hands-on on-call and data-quality reliability improvements.”

Distributed SystemsAPI DesignC#JavaKotlinPython+43
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DM

Debasish Mishra

Executive Engineering Leader specializing in Agentic AI and Generative AI

San Francisco, USA20y exp
mentorGenie.aiCornell University
Generative AIPredictive analyticsAnomaly detectionSentiment analysisModel fine-tuningData pipelines+63
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SS

Sravan Sama

Senior Machine Learning Engineer specializing in LLMs and scalable MLOps

San Francisco, CA7y exp
MetaIndiana University
A/B TestingAgileAmazon EC2Amazon EKSAmazon S3AWS+147
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DG

David Gao

Senior Software Engineer specializing in cloud architecture and AI/ML

Bellevue, WA15y exp
MicrosoftUSC
AgileAnalyticsAndroidAngularJSAnsibleApache Hadoop+63
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MK

Manasa Kalavakuri

Mid-level Data Scientist / GenAI & ML Engineer specializing in LLM apps and MLOps

Jersey City, NJ5y exp
MetaPace University
PythonPyTorchTensorFlowHugging Face TransformersLangChainOpenAI+76
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SA

Shilpa Akunuri

Executive Technology Leader specializing in SaaS platforms and Generative AI

San Francisco, CA18y exp
AmazonWharton School
A/B TestingAgileAngularAWSAWS CloudFormationAWS IAM+58
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NR

Nandivardhan Reddy

Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps

Dallas, TX6y exp
OpenAIUniversity of Texas at Dallas
A/B TestingApache HadoopApache HiveApache KafkaApache SparkArgo CD+98
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VS

Vishwam Shukla

Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and scalable inference

Seattle, WA6y exp
MetaNortheastern University
A/B TestingArgo CDAWSBashBigQueryC+++139
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DG

David Gao

Senior Software Engineer specializing in cloud architecture and machine learning

Bellevue, WA15y exp
MicrosoftUSC
AgileAnalyticsAndroidAnsibleApache CassandraApache Hadoop+59
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HV

Harsha vardhan

Senior Data Engineer specializing in cloud-native data platforms and streaming pipelines

7y exp
GoogleUniversity of Cincinnati
Azure Data FactoryAWSAmazon S3AWS LambdaAWS GlueAmazon EMR+94
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DA

Deepti Ahlawat

Mid-level Machine Learning Engineer specializing in Generative AI and LLM applications

USA6y exp
OpenAINJIT
PythonPyTorchTensorFlowHugging Face TransformersLangChainOpenAI+69
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NH

Nora Hu

Principal Software Engineering Manager specializing in cloud platforms and security

Palo Alto, CA20y exp
MicrosoftUniversity of Louisiana at Lafayette
AgileAzure Data FactoryC++CI/CDComplianceData Analysis+64
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KC

Kalyani Chittipolu

Screened

Mid-level Data Engineer specializing in AI/ML platforms and cloud data pipelines

USA4y exp
MetaTexas Tech University

“Built and shipped an LLM-powered data quality assistant that generates maintainable validation checks from metadata while executing validations via Great Expectations, exposed through FastAPI and integrated into Airflow-managed pipelines. Emphasizes production reliability (structured outputs, guardrails, monitoring, versioning, human review) and works closely with compliance/operations teams to deliver clear, auditable, user-friendly AI outputs.”

Machine LearningMLOpsData EngineeringData PipelinesETLData Ingestion+108
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AS

Akshitha Singireddy

Screened

Junior Software Engineer specializing in data engineering and computer vision

Bellevue, WA1y exp
AmazonCarnegie Mellon University

“Former Amazon intern who owned an end-to-end computer vision system to detect package anomalies in fulfillment centers, from data collection/labeling to production deployment on AWS (EC2/S3) with a Streamlit live-monitoring dashboard. Also has ML-in-production experience deploying and updating a recommendation model on Kubernetes (Minikube) with CI/CD via GitHub Actions, plus prior SDE experience with Jenkins-based pipelines and on-prem to AWS migration work using Glue.”

PythonJavaSQLJavaScriptHTMLCSS+66
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NP

Nishant Pathak

Screened

Executive Engineering Leader specializing in cloud-native platforms and security

14y exp
Kursaha TechnologiesIIT (BHU) Varanasi

“Former CTO of EzCred, a fintech embedded finance/digital lending infrastructure startup that built an API-first underwriting and servicing platform using alternative data (e.g., GST and bank statements) to cut loan decisions from days to minutes. Helped raise $1M in seed funding, built the engineering org and compliance-ready cloud architecture, and ran partner pilots before the company shut down during COVID-driven lending market contraction.”

AgileAndroidAngularJSAPI DesignAWSC+++87
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IH

ian holsman

Screened

Executive Engineering Leader (VP/CTO) specializing in Blockchain, DeFi, and FinTech platforms

Remote, USA19y exp
HederaMelbourne Business School

“CTO-focused candidate with experience at foundations evaluating startups, including reviewing technical architectures and coaching teams to refine ideas for better platform fit and synergies. Prioritizes company culture and integrity when choosing leadership roles.”

MicroservicesCloud Native ArchitectureDockerKubernetesCI/CDAutomated Testing+67
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RK

Ravikanth Kasamsetty

Screened

Executive AI/ML Engineering Leader specializing in cloud-native SaaS and GenAI platforms

23y exp
ServiceChannelPenn State University

“Engineering leader who modernized and unified a fragmented product suite at Milestone via a multi-year cloud-native roadmap, delivering an MVP in three quarters and boosting team velocity by 40% through cross-functional squads. At Prometheum, led a trust-building hybrid architecture (AWS control plane + customer-hosted data plane) using Kubernetes to ensure sensitive enterprise data never left customer networks while remaining cloud-agnostic across providers.”

Machine LearningArtificial IntelligenceGenerative AILarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)LLM Fine-Tuning+176
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SP

Sergey Pustovit

Screened

Director-level Data Platform & Analytics Engineering Leader specializing in distributed systems

Irvine, CA31y exp
SentinelOneNational University "Odessa Maritime Academy"

“Entrepreneurially minded builder focused on proving architecture concepts via minimal demo prototypes for marketing. Has hands-on experience improving an A/B experimentation framework by interviewing stakeholders, identifying system limits and bottlenecks, and defining success criteria to scale experimentation and speed up analysis.”

Budget ManagementRisk ManagementDistributed SystemsData WarehousingMicroservicesNoSQL+204
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