Vetted Data Transformation Professionals

“Built and owned an end-to-end AV operations automation and dashboarding platform for USC event operations, used daily to coordinate hundreds of live events. Delivered a React/TypeScript full-stack system integrating Smartsheet APIs with strong reliability practices (typed contracts, validation/fallbacks, safe rollouts) and experience with queue-based microservice patterns (idempotency, retries, DLQs, monitoring).”

“Analytics candidate with hands-on experience turning messy pricing and competitor data into reporting-ready SQL tables, plus building Python automation workflows that replaced manual processing across 40,000 images at roughly 89% accuracy. They also led a price elasticity analysis that informed differentiated pricing strategies and supported reporting through Power BI dashboards.”

“Worked on Sophia the humanoid robot, building production animation pipelines and enhancing human-robot interaction via perception and behavior orchestration. Experienced in stabilizing noisy perception-driven state transitions and designing smooth, user-centered behavioral flows, collaborating closely with artists, animators, and experience designers to translate creative intent into measurable system behavior.”

“Built and shipped a production LLM-powered healthcare support agent at UnitedHealthGroup, using LangChain + FAISS RAG on AWS SageMaker with CloudWatch monitoring and human-in-the-loop fallbacks for safety. Strong focus on reliability engineering (confidence gating, retries/timeouts, caching) and continuous evaluation loops; reported ~40% improvement in query resolution efficiency while reducing manual support workload.”

Nirmal Attarde

Screened

Mid-Level Software Development Engineer specializing in backend microservices and cloud

3y exp

“Software engineer with Oracle experience deploying a BioCatch fraud-detection integration into HDFC Bank’s core banking platform, using phased rollout and real-time monitoring and reporting ~80% fraud reduction. Also built a modular speech-to-text product (VocalSense AI) achieving ~95% accuracy and has strong production incident response skills (15-minute recovery) plus AWS serverless API hardening for messy inputs.”

“Analytics professional with experience spanning HSBC and the University of Buffalo, combining banking risk/portfolio analytics with reproducible Python and SQL reporting workflows. Stands out for cleaning complex multi-source data, standardizing business metrics across dashboards, and delivering measurable impact including an 80% reduction in manual reporting and an estimated GBP 1.2M profit contribution from scorecard redevelopment.”

“Analytics-focused candidate with hands-on experience using SQL, Python, and Power BI to turn fragmented event and user data into reliable reporting layers, automated workflows, and stakeholder-facing dashboards. They appear strongest in product/growth analytics, especially funnel, conversion, retention, and user behavior analysis, with clear examples of driving product improvements through metric design, segmentation, and ongoing monitoring.”

“Salesforce-focused candidate with hands-on experience owning Sales Cloud automation end to end, including requirements translation, Flow/Apex design, testing, and production deployment. They show practical judgment in choosing hybrid declarative/code solutions, bulk-safe Apex patterns, and modern UI work across both LWC and legacy Aura components.”

“Built and deployed a production LLM-powered RAG assistant for semiconductor manufacturing failure analysis, reducing engineer triage effort by grounding outputs in retrieved evidence and gating responses with SPC + ML signals (LSTM anomaly scores, XGBoost probabilities). Experienced with LangChain/LangGraph to ship reliable, observable multi-step agents with branching/fallback logic, and evaluates impact using both technical metrics and business KPIs like mean time to triage and downtime reduction.”

“Built and deployed a RAG-based clinical knowledge assistant at GE Healthcare to help clinicians query large volumes of messy, unstructured clinical documents with grounded, cited answers. Hands-on across the full stack (OCR/ETL, de-identification for PHI, Azure OpenAI embeddings, Cosmos DB indexing, FastAPI/Django) with production monitoring via LangSmith and performance tuning through batching and index optimization.”

“Data/ML practitioner with hands-on experience building NLP systems from prototype to production: delivered a Twitter sentiment classifier with robust preprocessing, SVM modeling, and Power BI reporting, and built entity-resolution pipelines for messy multi-source customer data (reporting ~95% improvement in unique entity identification). Also implemented semantic linking/search using SBERT embeddings with FAISS vector retrieval and domain fine-tuning (reported ~15% precision lift), and applies production workflow best practices (Airflow/Prefect, Docker, Azure ML/Databricks, Great Expectations).”

Ruthvik Bacha

Screened

Mid-level Data Engineer specializing in financial data pipelines and reliability

North Carolina, USA7y exp

“Systems/robotics-oriented software engineer focused on real-time orchestration and reliability: built a central control layer coordinating multiple concurrent agents with safe state machines, failure isolation, and recovery. Has hands-on ROS/ROS 2 integration experience in simulation (DDS/QoS, lifecycle, nodes in Python/C++) and emphasizes observability (structured JSON logs, correlation IDs) and low-latency control-loop performance under load.”

“Healthcare analytics professional with experience at UnitedHealth Group, focused on turning messy claims, eligibility, and provider data into clean reporting datasets and Power BI dashboards. Combines SQL and Python automation with strong stakeholder alignment around KPI definitions, helping operations teams improve claim turnaround visibility and cost efficiency.”

“Analytics candidate with hands-on experience at AT&T building SQL/Python pipelines for churn, usage, billing, and network-performance data at multi-million-row scale. Stands out for combining strong data quality and reconciliation practices with measurable operational impact, including a 30% query runtime improvement and ~8 hours/week of reporting automation savings.”

Harrishkumar Loganathan

Screened

Mid AI/Machine Learning Engineer specializing in FinTech and Generative AI

Remote, USA3y exp

“AI/ML engineer with hands-on ownership of enterprise LLM deployments at Freshworks, including a large-scale RAG chatbot serving 15,000+ users across six departments. Stands out for combining deep production engineering skills—AWS microservices, Kubernetes, observability, retrieval quality, and faithfulness evaluation—with strong cross-functional stakeholder leadership and prior large-scale fraud data pipeline experience at Socure.”

“Full-stack engineer with strong enterprise delivery experience across manufacturing and semiconductor use cases, owning deployments from discovery through post-launch support. Stands out for combining traditional product engineering with applied GenAI workflows and data pipeline reliability work, including a manufacturing app that reportedly saved a Fortune 500 customer about $6M and an AI chat panel adopted by 70% of pricing analysts.”

“Engineer with banking and industrial/IoT experience who has deployed a payment-processing microservice with zero downtime, handling Protobuf schema evolution and sensitive data migration via dual-write/checksum techniques. Demonstrates strong cross-stack troubleshooting (pinpointed intermittent distributed timeouts to a failing ToR switch port) and customer-facing Python ETL customization using plugin-based parsers and Pydantic validation, plus hands-on monitoring/alerting improvements with operators.”

“Data/ML practitioner with experience applying NLP and classical ML to large-scale customer data (2B+ records) for segmentation, prediction, and survey-text classification, delivering measurable business impact (~18% engagement efficiency). Has hands-on entity resolution across multi-source datasets and has built embedding-based semantic search using SentenceBERT + a vector database with domain fine-tuning (~20% relevance improvement), plus production workflow experience with Spark/Airflow and cloud tooling (AWS/Azure).”

“AWS Solutions Architect intern who advised customers on securing a multi-tenant LLM-based SaaS, including isolation strategy tradeoffs and production guardrails against prompt injection. Has experience investigating a prompt-injection incident using logs/traces and TTP-style documentation, and designing scalable SDK/agent integrations via asynchronous worker architecture with prompt versioning.”

“AI/software engineer with experience at Visa building a real-time transaction fraud/risk scoring microservice in the card authorization path (Python, Kafka, Kubernetes on AWS) with strict 120–150ms latency constraints and reason-code outputs for downstream decisioning. Owns ML backend end-to-end (data/feature engineering, model training, deployment) and has demonstrated production reliability work including latency spike mitigation, SLO-based observability, drift monitoring, and safe fallbacks to rule-based decisions.”

“Healthcare GenAI engineer who built a HIPAA-compliant, auditable RAG-based claims decision support system at Molina Healthcare, processing 3M claims and delivering major impact (48% faster manual reviews, 43% higher decision accuracy). Deep hands-on experience with LangChain orchestration, vector search (ChromaDB/FAISS), embedding fine-tuning, and safety controls (confidence scoring, rule validation, human-in-the-loop escalation) for clinical workflows.”

“Data engineer/platform builder with experience across PwC and Liberty Mutual delivering high-volume, production-grade pipelines and real-time data services. Has owned end-to-end streaming + batch architectures on AWS and Azure, including web scraping systems, with quantified reliability gains (99.9% availability, 90%+ error reduction, 30% latency reduction) and strong observability/CI-CD practices.”

Shangyi Chen

Screened

Mid-Level Full-Stack Software Engineer specializing in Java and Angular web applications

San Francisco, CA5y exp

“Full-stack engineer who has owned end-to-end delivery of an internal, customer-facing data visualization product and helped build a data modification pipeline used across the organization for data integrity/governance. Demonstrates pragmatic MVP-driven delivery within sprints and makes performance-oriented architectural decisions (e.g., batching API calls to reduce frontend request volume) in TypeScript/React systems.”

Bhavyasree Chinthala

Screened

Mid-level Data Engineer specializing in cloud data pipelines and real-time streaming

USA, USA5y exp

“Data engineer with PNC Bank experience owning high-volume financial transaction pipelines end-to-end (Kafka/REST ingestion through Spark/Glue transformations to Redshift serving) for risk and fraud analytics. Built strong reliability and data quality practices (Great Expectations, reconciliation, Airflow alerting, idempotent retries, incremental/windowed processing), reporting 40% ingestion efficiency gains and ~99.9% data accuracy.”