Vetted Oracle Database Professionals

Jaya Rathi

Screened

Senior Software Engineer specializing in distributed systems and cloud platforms

Ottawa, Canada15y exp

“Software professional with 13 years of experience across Canada and India, now seeking a first US role in California. Has practical experience applying LLMs and IDE agents like Cursor, ChatGPT, and Gemini to streamline engineering documentation workflows, especially automating Jira/Confluence process work to reduce manual effort and errors.”

Jessy Kattupalli

Screened

Mid-level Full-Stack Java Developer specializing in enterprise web applications

West Haven, CT4y exp

“Backend/full-stack engineer with hands-on experience building enterprise-scale real-time log analysis platforms using Spring Boot, Kafka, React, and observability tooling. Stands out for using AI tools heavily but responsibly—treating them as accelerators while relying on rigorous testing, architectural review, retry/DLQ patterns, and monitoring to ensure production reliability.”

Nicholas Leytem

Screened

Staff Software Engineer specializing in high-throughput retail data systems

Minneapolis, MN12y exp

“Software engineer at a global public growth company since 2015, with experience owning a legacy Java ETL analytics application and helping design and launch a Kotlin/Java data sourcing platform for customer order data. Brings hands-on experience across React, Spring Boot, AWS/Kubernetes deployment, and multi-database architectures, including an inventive pseudo-graph implementation in DynamoDB to support flexible document matching.”

“Full-stack/product-minded engineer with strong distributed systems depth, spanning Spring Boot/Kafka microservices, Kubernetes observability, and large-scale React/TypeScript frontends. Particularly compelling for teams building real-time operational products: they describe owning payment/inventory services, designing telemetry dashboards for 150+ services, and helping move claims tracking from polling to event-driven architecture.”

“Engineer with experience in small, high-pressure innovation environments and enterprise healthcare platforms, spanning distributed systems, search, and database optimization. At RJ Lee Group, he helped pivot an Air Force document-processing platform from Pig/MapReduce to Apache Storm, enabling near-real-time results, and also built a full-stack natural-language search application that cut analyst investigations from months to weeks or days.”

“Backend/platform engineer from Dune Security with strong experience turning messy, fragmented workflows into reusable production systems. They’ve built a shared database abstraction layer, integrated multiple enterprise security platforms into a unified workflow, and shipped AWS Bedrock-powered security insight features with guardrails and human review.”

“Data/analytics-focused engineer who builds end-to-end KPI reporting and validation products used daily by plant leads and leadership to track yield, downtime, and defects. Combines Python/SQL + Power BI data pipelines with strong data-quality practices (automated validation, monitoring/alerts) and has experience designing scalable frontend architecture in TypeScript/React and working in distributed/microservices-style data systems.”

“Runs two lean real estate companies remotely by building local on-the-ground contact networks and leveraging free-tier technology to keep total annual business costs under $100. Brings a cost-elimination and MVP/validation-first mindset, preferring to join an established company unless a clearly viable business idea emerges.”

“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.”

“Global Talent Acquisition Operations leader with ~10 years leading TA strategy across North America, EMEA, and APAC; built and manages a 14-person worldwide TA team at Computershare. Known for modernizing recruiting operations with AI-driven sourcing, market intelligence (TalentNeuron), and digital interviewing—most notably redesigning India hiring workflows to cut time-to-fill by 35%—and for leading major ATS transformation work including Oracle Taleo to Oracle Fusion migration with UAT and hypercare.”

“Backend-focused Python/Flask engineer with strong performance and scalability experience across PostgreSQL/SQLAlchemy optimization, caching, and async processing. Has implemented multi-tenant data isolation (schema/db per tenant with RBAC and encryption) and integrated TensorFlow-based ML inference behind a Flask REST API using Redis caching, batching, and async execution; reports measurable wins like cutting endpoints from 6–8s to ~2s and increasing throughput 3–4x via Celery queues.”

“Hands-on engineering manager/lead focused on Azure application deployments and CI/CD automation. Has led design sessions and 1:1 code reviews, and owned a production performance incident end-to-end from measurement and test-environment setup through production validation, while coaching team members via regular 1:1s.”

“Data/MLOps engineer (Cognizant background) who owned an AWS/Airflow/Snowflake healthcare transactions pipeline processing ~8–10M records/day and cut pipeline/data-quality incidents by ~33%. Also built and deployed a production FastAPI model-inference service on Kubernetes (Docker, HPA) with strong observability (Prometheus/Grafana), versioned endpoints, and resilient backfill/idempotent external data ingestion patterns.”

“Backend/data engineer focused on AWS-based, event-driven systems—building Golang microservices and serverless pipelines with strong data validation, observability (CloudWatch/Splunk/New Relic), and reliability patterns (retries/DLQs). Has also operated distributed web scraping/data collection with schema versioning and Step Functions backfills, and ships well-documented, versioned REST/WebSocket APIs for internal and external consumers.”

Sri Lalitha

Screened

Senior Full-Stack Java Engineer specializing in cloud-native microservices and FinTech

California, USA6y exp

“Backend engineer who owned a Python task management API with JWT auth, async notifications, and performance work (DB optimization/caching) to handle high volumes. Led an on-prem to Azure private cloud migration at Morgan Stanley using GitOps and IaC (Terraform/ARM) with phased rollout and rollback planning. Also built a Kafka real-time streaming pipeline with exactly-once/idempotent consumers and Prometheus/Grafana monitoring.”

Manasa Reddy Nagendla

Screened

Mid-level Full-Stack Java Engineer specializing in microservices, cloud, and event-driven systems

Cincinnati, OH6y exp

“Software engineer at Procter & Gamble focused on warehouse/operations systems, building near-real-time order/inventory visibility using Java/Spring Boot, React, Kafka, PostgreSQL, and Redis with measurable latency and load-time gains. Also shipped internal LLM/RAG knowledge assistants grounded in company runbooks and workflows, implementing guardrails and an evaluation loop that drove concrete retrieval improvements (document chunking) and regression prevention.”

Saikrishna Vallala

Screened

Mid-level QA Automation Engineer / SDET specializing in Financial Services and Healthcare

USA5y exp

“Fintech-focused engineer who built an end-to-end KYC verification pipeline for advisor onboarding using Flask microservices, Celery/Redis, and AWS (Lambda/ECS/EC2) with CloudWatch-driven scaling and latency optimizations. Also shipped a production internal knowledge assistant using RAG + embeddings/vector search with guardrails (similarity-based fallback, prompt-injection protections) and an evaluation loop with compliance specialist review that drove measurable retrieval improvements.”

Soham Patil

Screened

Junior Cloud & AI/ML Engineer specializing in AWS GovCloud and MLOps

Washington, DC2y exp

“Robotics software engineer with hands-on ROS 2 autonomy experience on an obstacle-avoiding quadrotor (ROS 2 + Gazebo + PX4 + Nav2/SLAM), including custom work to extend Nav2 into a 3D aerial domain and output PX4 trajectory setpoints. Also built cost-saving ML infrastructure (PostgreSQL + AWS data-cleaning pipeline) and improved object detection accuracy by 40% using CUDA/PyTorch, with strong containerization and CI/CD practices (Docker + Kubernetes, aggressive version pinning) to prevent environment drift.”

Narendra R

Screened

Senior Full-Stack Java Developer specializing in microservices and cloud platforms

Dallas, TX7y exp

“Backend engineer focused on scalable Python/Flask services and high-performance PostgreSQL/SQLAlchemy systems, with demonstrated wins like reducing N+1-driven response times to under 200ms and cutting P95 latency below 1s via background queues and caching. Has production experience operationalizing ML models as Dockerized APIs on AWS (S3/Lambda) with monitoring (CloudWatch/ELK), plus robust multi-tenant isolation using JWT-driven tenant context and row-level security.”

Meghanath kethireddy

Screened

Mid-level Full-Stack/Backend Engineer specializing in Java microservices and cloud platforms

Dallas, TX5y exp

“PayPal ML/AI practitioner who built and productionized a hybrid recommendation engine (BERT/LLM embeddings + collaborative filtering + XGBoost ranking) on AWS with end-to-end MLOps and orchestration. Addressed real-world issues like cold start and embedding latency (ONNX, clustering, caching, PySpark/Delta Lake) and drove a 27% lift in upsell conversion via A/B testing and stakeholder collaboration with marketing.”

“Data engineer with experience at Capital One and HSBC building and operating GCP-based data platforms. Led an end-to-end Oracle-to-BigQuery migration processing ~200–300GB/day using Dataflow/Beam, Airflow, Dataproc/PySpark, and Looker, achieving ~99.5% pipeline success and ~30% fewer data quality issues. Strong in production reliability, schema drift handling for external APIs, and BigQuery performance/serving patterns (materialized views, authorized views, versioned datasets).”

Sukesh Anamaneni

Screened

Senior Business Analyst specializing in AI and commercial banking analytics

Detroit, MI5y exp

“Analytics candidate with hands-on experience supporting a workforce system transformation from symplr to Oracle Fusion Time and Labor, using SQL and Python to turn operational HR, attendance, and payroll data into reporting-ready datasets. They emphasize performance optimization, reusable analytics pipelines, and metric consistency across dashboards, with project work focused on overtime reduction, workforce efficiency, and retention trends by department.”

Dhriti Kanchan

Screened

Mid-level Data Analyst specializing in healthcare and financial analytics

Texas, USA5y exp

“Analytics-focused candidate with hands-on experience turning messy CRM, e-commerce, payments, and support data into trusted reporting datasets using SQL and Python. They have owned end-to-end churn and retention analytics work, including RFM-based segmentation, dashboard delivery, and metric standardization across sales, marketing, and finance.”

Rohit Vibhu Channananjundarya

Screened

Mid-level Software Engineer specializing in distributed systems and full-stack platforms

Chicago, IL6y exp

“Engineer who treats AI as a force multiplier rather than a replacement for judgment, with hands-on experience using tools like Claude Code, Cursor, Copilot, and Codex across planning, coding, testing, and review. Particularly notable for building a multi-agent PR review system that automated summarization, risk scanning, schema validation, and test suggestions, helping the team shift reviewer time toward architecture and business logic.”