Pre-screened and vetted.
Mid-level Data Engineer specializing in cloud ETL/ELT and lakehouse architecture
“Data engineer focused on sales/marketing analytics pipelines, owning ingestion from CRMs/ad platforms through warehouse serving and dashboards at ~hundreds of thousands of records/day. Built reliability-focused systems including dbt/SQL/Python data quality gates with alerting, a resilient web-scraping pipeline (retries/backoff, anti-bot tactics, schema-change detection, backfills), and a versioned internal REST API with caching and strong developer usability.”
Mid-level Data Engineer specializing in real-time streaming and cloud data platforms
“Data engineer with Wells Fargo experience owning an end-to-end lakehouse ETL pipeline on Databricks/Azure Data Factory, processing ~480GB daily and implementing robust data quality/reconciliation across 40+ tables to reach ~99.3% reliability. Strong in performance optimization (cut runtime 5.5h→3.8h), CI/CD and monitoring, and resilient external/API ingestion with retries, schema validation, and backfills.”
Mid-level Data Scientist specializing in LLMs, RAG, and document intelligence
“LLM/ML engineer who has shipped production systems in legal/financial-risk domains at Wolters Kluwer, including a hybrid OCR+deterministic+LLM extraction pipeline that structured UCC filings at massive scale and drove $6M+ in revenue. Also built LangGraph-based multi-agent “Deep Research” workflows with model routing, tool calls (MCP), persistence, and human-in-the-loop review, and partnered closely with policy writers to deliver LLM summarization that cut writing time by ~60%.”
Mid-level Data Engineer specializing in AWS cloud data platforms
“Data engineer with Charter Communications experience modernizing large-scale AWS data lake pipelines: ingesting S3 data, validating against legacy systems, transforming with PySpark/Spark SQL, and serving via Iceberg/Delta tables. Worked at 50M–300M record scale, delivered >99.5% data match, and built monitoring/alerting (CloudWatch/SNS) plus retry orchestration (Step Functions) and data quality gates (Great Expectations).”
Mid-Level Full-Stack Python Developer specializing in AI and data platforms
“Full-stack engineer who builds TypeScript/React SPAs on Python (Flask/FastAPI) backends and has hands-on experience integrating AI components (Azure OpenAI, LangChain, vector databases) into user workflows. Has built internal AI-enabled dashboards/search tools for analysts and business users, emphasizing typed API contracts, CI/CD-driven quality, and microservices reliability patterns (monitoring, retries, idempotency) at scale.”
Mid-level Full-Stack Developer specializing in React and scalable web applications
“Backend/data engineer with hands-on production experience across FastAPI microservices and AWS data platforms. Has delivered serverless and Glue/EMR-based ETL pipelines with strong observability (Prometheus/Grafana/Sentry, CloudWatch/SNS), schema-evolution resilience, and measurable SQL performance wins (5 min to <30 sec). Open to onsite meetings in the Bethesda, MD area and flexible on remote arrangements.”
Senior Data Engineer specializing in cloud data platforms and real-time analytics
“Data engineer (Credit One) who built and owned real-time financial transaction and credit risk/fraud data systems end-to-end on AWS + Snowflake. Delivered high-scale pipelines (150k events/hour; ~2TB/week), raised data accuracy to 99%, and cut Snowflake costs 42% while adding strong observability, schema-drift handling, and production-grade APIs/documentation.”
Senior Full-Stack Engineer specializing in Java microservices and cloud-native web apps
“Backend/full-stack engineer who has owned production retail and order/inventory systems end-to-end, using Spring Boot microservices with Kafka event-driven workflows. Strong in production correctness patterns (idempotency, retries/DLQs, schema versioning) plus observability (Prometheus/Grafana) and developer-facing API design (Swagger, OAuth2/JWT, versioning/deprecation). Also built TypeScript/React SPAs and cited ~40% UI performance improvement.”
Mid-level AI Engineer specializing in ML platforms, recommender systems, and GenAI/RAG
Senior Full-Stack Engineer specializing in cloud-native platforms and data engineering
Senior DevOps Engineer specializing in multi-cloud, Kubernetes, and GitOps
Mid-level Data Engineer specializing in AWS data platforms and streaming pipelines
Senior ML/AI Software Engineer specializing in GenAI, RAG, and cloud-native MLOps
Principal Software Engineer specializing in AI/ML, big data, and FinTech
Mid-level AI/ML Engineer & Data Scientist specializing in recommender systems and MLOps
Senior Data Engineer specializing in cloud data platforms and ETL/ELT pipelines
Senior Data Engineer specializing in cloud data pipelines and real-time streaming
Mid-level Data Engineer specializing in streaming analytics and ML pipelines
Mid-level Data Engineer specializing in cloud data pipelines and big data platforms
Mid-level Cloud Data Engineer specializing in AWS lakehouse and streaming analytics
Senior AI Engineer specializing in Generative AI, RAG, and agentic LLM platforms