Vetted Tableau Professionals

Uday kumar swamy

Screened

Senior Machine Learning Engineer specializing in MLOps and NLP/GenAI

Chicago, USA9y exp

“Built a production LLM-agent framework for a startup that performs daily financial/trading analysis by combining live market data with internal tools, including a centralized memory module to prevent context drift and reduce hallucinations. Also implemented an Airflow-orchestrated retail price forecasting pipeline deployed to AWS endpoints, scaling parallel workloads via Kubernetes Executor and validating systems with rigorous functional + LLM-specific metrics and cross-team collaboration.”

UMESH KAMISETTY

Screened

Mid-level Data Engineer specializing in cloud lakehouse and streaming platforms

Seattle, WA5y exp

“Data engineer focused on building production-grade pipelines on AWS (Kafka/Kinesis/Glue/S3) through to curated serving layers in Snowflake and Delta Lake. Emphasizes automated data quality validation (PySpark + CI/CD), modular dbt transformations for analytics (customer spending, risk metrics), and operational reliability with CloudWatch and DLQs; data consumed by BI tools and ML pipelines for fraud detection and risk analytics.”

Harshitha Parupalli

Screened

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

Jersey City, NJ4y exp

“Data engineer with healthcare domain experience who owned 100M+ record pipelines end-to-end (Kafka/Kinesis/ADF → PySpark/dbt validation → Spark SQL transforms → Snowflake/Power BI serving). Built production-grade reliability practices (Airflow orchestration, CloudWatch/Grafana monitoring, pytest + contract/regression tests, idempotent ingestion/backfills) and delivered measurable improvements: 35% lower latency and 40% better query performance.”

“Data/streaming engineer in capital markets who led an end-to-end trade settlement data product (Kafka→MongoDB→data lake) with rigorous data-quality logic and ~$175K first-year operational impact. Also built a low-latency Go-based CME market data engine feeding SOFR curve generation, using MSK on EKS with performance tuning (idempotency, compression, partitioning) to achieve sub-100ms delivery.”

“Healthcare analytics candidate with hands-on experience turning messy claims data in Redshift and S3 into validated reporting tables, plus automating KPI workflows in Python. They’ve owned end-to-end operational analytics projects, including a claims delay analysis that improved processing efficiency by about 20%, and have experience driving stakeholder adoption of standardized metrics across dashboards.”

MOUNIKA SAI MEKALA

Screened

Junior Data Analyst specializing in financial and operational analytics

Kansas, USA3y exp

“Analytics professional with experience at KPMG turning messy operational and financial data from SQL Server and AWS S3 into clean reporting datasets and automated Python workflows. They combine SQL, Python, Power BI, and experimentation methods to deliver stakeholder-aligned KPI dashboards and marketing performance insights with a strong focus on data integrity and reproducibility.”

“Master’s in Business Analytics candidate with hands-on project experience spanning FMCG sales analytics, insurance risk modeling, and HR attrition analysis. Demonstrates strong SQL and Python fundamentals, including advanced CTE/window-function work, reproducible modeling workflows, and Power BI dashboards that translate analysis into clear business actions.”

“Analytics professional with experience at Franklin Templeton and IQVIA India, focused on turning messy cross-system data into trusted reporting and actionable business insights. Stands out for combining SQL, Python, AWS ETL, and BI dashboards to solve data quality issues, improve investor engagement analysis, and standardize commercial reporting in financial services and pharma contexts.”

“Business/data analyst with experience at KPMG and Liberty Mutual, focused on financial reporting, data quality, and analytics automation. Has built SQL and Python workflows for large transaction datasets, reduced manual reporting effort by 15+ hours per week, and translated ambiguous business questions into standardized KPIs and Power BI dashboards used for decision-making.”

SAITEJA MALLEMPUDI

Screened

Senior Data Scientist and AI/ML Engineer specializing in GenAI and cloud ML

Chicago, IL6y exp

“ML/AI engineer with hands-on experience owning systems from experimentation through deployment and monitoring, including a Bank of Montreal project that improved timely interventions by 12%. Also brings GenAI/RAG experience with evaluation and safety guardrails, plus clinical NLP pipeline work extracting medication data from notes for patient risk prediction.”

Scott Evans

Screened

Director-level Product Leader specializing in platforms, marketplaces, workflow automation, and AI

Indianapolis, IN10y exp

“Product leader with experience across marketplaces, AI/ML operations products, and education-focused research. Led the Angi native app rebuild that generated $5M+ in revenue, shipped an OCR/ML title-processing product at Cox, and is now focused on K-12 workforce pathways and human-centered AI.”

Matthew Marriotti

Screened

Director-level Product and UX leader specializing in retail e-commerce experiences

Erie, PA13y exp

“Long-tenured American Eagle product/design leader with 12.5 years driving digital experience transformation, including a zero-to-one mobile app initiative that grew from less than 5% to more than 50% of digital revenue. Brings a rare blend of UX research depth, product strategy, cross-functional execution, and practical AI-enabled design thinking.”

“B2B SaaS presales/solutions engineer with recent experience spanning Cisco enterprise infrastructure and AI-driven POS analytics products. Supported 120+ enterprise accounts, helped drive a $10M renewal/expansion in financial services, and combines classic enterprise SE skills with hands-on API, SSO/SAML, ETL, Python, SQL, and LLM/RAG integration experience.”

“Early-career solutions engineer with experience spanning Dell Technologies and insurance operations, combining enterprise hybrid cloud pre-sales exposure with hands-on AI and API integration work. Completed a master's at Illinois Institute of Technology while building customer-facing experience in technical discovery, POCs, security/compliance discussions, and workflow automation.”

Emily MacPherson

Screened

Senior finance and business operations leader specializing in technology financial management

San Francisco, CA14y exp

“Finance leader with roots in telecom and utilities who evolved from FP&A and product analysis into strategic technology business management. They have built cost transparency and total-cost-of-ownership capabilities for large-scale agile product transformations, delivering $41M in expense impact and helping reprioritize $200M+ in capital investments.”

Praveenkumar Angadi

Screened

Director-level telecom sales and solutions leader specializing in AI and 5G

Austin, TX23y exp

“Heads an innovation center at Wipro Technologies and has built go-to-market motions for enterprise private 5G solutions in partnership with Google Cloud, Verizon, and AT&T. Brings a distinctive blend of strategy, partner orchestration, and enterprise deal execution across manufacturing and automotive customers, with experience tailoring tiered offerings and using digital twins to drive pipeline.”

“Toronto-raised hockey player with experience in the GTHL and college hockey at UNC Chapel Hill who now works in the NHL focused on hockey analytics. Leverages a broad network across high school, college, and pro levels plus marketing/NIL awareness to advise players on development, recruiting outreach, and team/coach fit.”

“Backend/data engineer with production experience building secure Django/DRF APIs (JWT RS256 + rotating refresh tokens), background processing with Celery, and strong reliability practices (timeouts, retries/backoff, structured logging, audit trails). Has delivered AWS solutions spanning Lambda + ECS with IaC/CI-CD and built Glue/PySpark ETL pipelines with schema evolution and data-quality quarantine patterns; also modernized a legacy SAS pipeline to Python/PySpark with parallel-run parity validation and phased rollout.”

“Built and deployed a production long-form article summarization system using BART/T5/PEGASUS, tackling real-world constraints like token limits, latency/quality tradeoffs, and factual drift via chunking/merge logic and constrained decoding. Uses pragmatic Python-based pipeline orchestration (scheduled jobs, modular scripts, logging/retries) and iterates with stakeholder feedback to make outputs genuinely useful for content workflows.”

“LLM/ML platform engineer with hands-on experience taking an LLM document summarization prototype into a production-grade service on AWS EKS, emphasizing low-latency inference, drift monitoring, and safe CI/CD rollouts (canary + rollback). Strong in real-time debugging of agentic/RAG systems (tracing, retrieval/index drift fixes) and in developer enablement through practical workshops (Docker/Kubernetes/FastAPI) plus pre-sales support via demos and benchmarks to close pilots.”

“Built and deployed production LLM-powered document summarization/classification systems using embeddings, vector databases (RAG-style retrieval), and automated evaluation (BERTScore/ROUGE), with a focus on monitoring and scalable cloud pipelines. Also partnered with a fraud analytics team to deliver a transaction anomaly detection solution, translating model outputs into Power BI dashboards and actionable KPIs while iterating on thresholds and alerts based on stakeholder feedback.”

“Healthcare data/ML practitioner with experience at UnitedHealth Group building production ETL and streaming pipelines (Python, BigQuery, Kafka) that unify EHR, IoT device, and lab data for patient risk prediction. Also implemented embedding-based semantic search/linking for noisy clinical notes via domain adaptation and rigorous validation with clinical stakeholders; previously built churn prediction at DirecTV using XGBoost.”

“Built and shipped LLM/RAG systems in finance and startup settings, including a Goldman Sachs document intelligence platform that indexed ~8TB of regulatory filings and delivered cited, conversational answers with <2s latency—cutting compliance research by ~4.5 hours per batch. Also developed LangChain-based agent workflows at Finta to automate CRM enrichment and investor lookup with strong testing, tracing (LangSmith), privacy guardrails, and auditability.”