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Kelvin Danyal

@kelvindanyal

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Senior data engineer turning messy data into trusted, cloud-native streaming and ETL platforms.

United States

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What I'm looking for

I’m looking to own end-to-end streaming and analytics data platforms—prioritizing zero data-loss reliability, fast delivery, strong data quality checks, and HIPAA-grade compliance—while partnering with analysts and ML teams to scale impact.

Senior Data Engineer with 12+ years designing and managing lakehouse platforms and real-time streaming pipelines. Expert in Spark, Flink, Kafka, Delta Lake, Iceberg, Snowflake, and Databricks. Skilled in AI/ML pipelines, LLM and RAG workflows, vector databases, and cloud-native healthcare data platforms. Proven record processing billions of events daily with 99.9%+ uptime

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Techinoxsystems

Apr 2023 - Present (3 years 2 months)

Led a lakehouse platform supporting 2B+ events/day across 3 AWS regions for 50+ analysts and 10 ML models, cutting batch lag from 8 hours to 2 minutes. Built Kinesis+Lambda+Iceberg streaming pipelines, created 350 dbt models with automated freshness checks, implemented HIPAA-compliant PII detection (99.7% accuracy), and optimized Snowflake to save $45k/month.

Apache Spark Amazon Kinesis AWS Lambda Apache Kafka Apache Iceberg DBT Snowflake CI CD

Senior Data Engineer

Centric Consulting

Jun 2020 - Mar 2023 (2 years 9 months)

Delivered streaming and batch pipelines for enterprise clients across retail, insurance, and manufacturing. Built a customer-360 warehouse integrating Shopify, Salesforce, and Google Analytics for 30 analysts, and reduced pipeline development time from 2 weeks to 3 days using reusable Airflow templates while catching 95% of schema issues pre-production.

Apache Kafka Apache Airflow Shopify Salesforce Google Analytics

Senior Data Engineer

Flatiron Health

Sep 2018 - May 2020 (1 year 8 months)

Maintained ETL pipelines for oncology real-world data from 280 community practices and built EHR data abstraction pipelines using Spark and NLP. Engineered Delta Lake and Databricks lakehouse solutions for structured and unstructured clinical datasets, designed clinical RAG pipelines that improved document retrieval 15x, and reduced research-ready dataset prep from 6 weeks to 5 days through mentor