Vetted Apache Hadoop Professionals

Pre-screened and vetted.

SS

Executive Technology Leader (CTO) specializing in AI-enabled SaaS and cloud transformation

Austin, TX18y exp
Eagle Venture StudioUniversity of Texas at Arlington
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AM

Mid-level Data Engineer specializing in cloud-native ETL/ELT and Snowflake analytics platforms

Tennessee, USA5y exp
McKessonUniversity of Memphis
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SS

Mid-level Data Engineer specializing in cloud data platforms and BI analytics

Remote, USA4y exp
U.S. BankSan José State University
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AS

Mid-level Data Engineer specializing in cloud lakehouse and streaming analytics for financial services

New York, NY3y exp
AccentureUniversity of Alabama at Birmingham
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MK

Mid-level Data Engineer specializing in cloud data pipelines and analytics (AWS/Azure)

Fairfax, VA4y exp
AllstateGeorge Mason University
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BG

Mid-level Data Engineer specializing in cloud ETL, streaming, and ML-ready data pipelines

Boise, ID5y exp
AlbertsonsTexas State University
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SB

Mid-level Data Engineer specializing in big data pipelines and cloud data platforms

Dallas, TX6y exp
HoneywellEast Texas A&M University
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SB

Mid-level Business Analyst specializing in cloud data analytics

5y exp
TargetSaint Leo University
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AJ

Senior Data Analyst specializing in data governance and analytics

New York, NY12y exp
Publishers Clearing HouseUniversity at Buffalo
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MC

Senior Data Scientist specializing in ML engineering and cloud analytics

Calgary, Canada8y exp
Geek Inc.Georgia Tech
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KC

Senior AI/ML Engineer specializing in MLOps and Generative AI (LLMs/RAG)

Chicago, IL10y exp
United Airlines
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PM

Mid-level Data Scientist specializing in ML, NLP, and LLM-powered analytics

Westlake, OH4y exp
KeyBank
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BR

Bharath Reddy Nallu

Screened ReferencesStrong rec.

Mid-level Machine Learning Engineer specializing in NLP and scalable MLOps

4y exp
Northern TrustUniversity of the Cumberlands

Data/ML engineer in financial services (Northern Trust) who built a production RAG-based LLM system to connect structured transaction/portfolio data with unstructured market and internal documents for risk teams. Strong in end-to-end pipelines (AWS Glue/Airflow/PySpark), entity resolution, and taking models from prototype to reliable daily production with performance tuning (LoRA + TensorRT) and monitoring.

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SM

Sai Manikanta Kasireddy

Screened ReferencesStrong rec.

Mid-level Machine Learning Engineer specializing in cloud-native GenAI and RAG systems

5y exp
Revstar ConsultingUniversity of North Texas

Built and productionized an internal GenAI chatbot that makes company policy/SOP knowledge instantly searchable, using a secure RAG architecture on AWS (Bedrock/Titan embeddings/OpenSearch Serverless, Textract/Lambda/S3 ingestion, Claude 3 Sonnet). Demonstrates strong MLOps/orchestration experience (Airflow, Step Functions with Lambda/Glue/SageMaker) and a rigorous reliability approach (RAGAS metrics, A/B testing, citation validation, monitoring), including collaboration with compliance stakeholders via review dashboards.

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PK

Praniket Ketan Walavalkar

Screened ReferencesStrong rec.

Junior AI Software Engineer specializing in RAG agents and cloud data platforms

Seattle, WA1y exp
University of WashingtonUniversity of Washington

AI Software Engineer (student employee) at University of Washington IT who helped deploy "Purple," a governed, explainable LLM platform on Azure used by 100,000+ students/faculty/staff. Independently led scalable reliability efforts by building automated agent quality/load/red-team testing and CI/CD health validation (Playwright/Node.js, Azure DevOps), and previously built an explainable AI scheduling assistant for clinical operations at Proliance Surgeons.

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KI

Khuram Ismaeel

Screened ReferencesModerate rec.

Senior AI/ML Engineer specializing in machine learning and cloud-native AI systems

10y exp
SoftServeAir University

ML/AI engineer with hands-on ownership of production recommendation and GenAI systems, spanning experimentation, deployment, monitoring, and iteration. Stands out for delivering measurable outcomes—22% CTR lift, 15% conversion lift, and a 30% reduction in support tickets—while demonstrating strong judgment on latency, cost, and safety tradeoffs in real-world systems.

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Preetham Dandu - Junior Software Engineer specializing in backend, distributed systems, and cloud platforms in Stony Brook, NY

Preetham Dandu

Screened ReferencesModerate rec.

Junior Software Engineer specializing in backend, distributed systems, and cloud platforms

Stony Brook, NY1y exp
Stony Brook UniversityStony Brook University

MS candidate with strong backend/data engineering focus who builds research and data systems with production-grade rigor (reproducibility, observability, restartability). Has hands-on experience securing and scaling FastAPI-based gateways in front of Java microservices, leading SQL Server→Snowflake migrations with dual-write/feature-flag rollouts, and hardening Kafka-based fleet-tracking systems against out-of-order and duplicate events.

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Shane Weinstock - Senior Data Scientist & Product Analytics Leader specializing in ML and experimentation in Austin, TX

Senior Data Scientist & Product Analytics Leader specializing in ML and experimentation

Austin, TX17y exp
OctaveSouthern Methodist University

Aspiring founder with ~15 years of experience across varied backgrounds, motivated by frustration with slow, change-resistant large organizations and a desire to bring innovative ideas to market. Familiar with how venture capital/accelerators function (though not directly worked in them) and expresses strong willingness to take entrepreneurial risks.

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RG

Rishabhh Garg

Screened

Software Engineer specializing in full-stack development and AI/ML automation

Needham, MA4y exp
First Help FinancialNortheastern University

Backend Python engineer focused on production-grade automation and reliability, with hands-on experience designing scalable API systems on PostgreSQL and making pragmatic architecture calls (modular monolith over premature microservices). Demonstrated measurable performance wins (50–60% latency reduction) and strong operational rigor via observability, incremental rollouts/feature flags, and security patterns like JWT + RBAC + database row-level security.

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SM

Mid-level Data Scientist specializing in ML and Generative AI (LLMs, NLP, Computer Vision)

FL, USA6y exp
Spirit AirlinesColorado State University
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LK

Mid-level AI/ML Engineer specializing in NLP, LLMs, and MLOps

USA4y exp
Cardinal HealthUniversity of Texas at Arlington
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SL

Mid-level AI/ML Engineer specializing in generative AI and MLOps

Remote, USA5y exp
MizuhoAuburn University at Montgomery
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