Open to opportunities

Deepak Dulal

@deepakdulal

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Senior Data Engineer/Scientist driving scalable cloud-native data and ML solutions.

United States

Message

What I'm looking for

I seek senior roles building cloud-native, real-time data platforms and ML productionization, working cross-functionally to deliver measurable business impact in an agile environment.

I am a Senior Data Engineer/Scientist with six years of experience building scalable, cloud-native data and ML solutions across AWS, Azure, and GCP. I design end-to-end ETL pipelines, real-time streaming architectures, and CI/CD frameworks to deliver production-grade analytics.

I have engineered real-time streaming systems that reduced fraud detection and monitoring latency to sub-second levels, modernized mainframe-to-cloud migrations to Snowflake, improved forecasting accuracy by up to 30%, and cut ETL runtimes by as much as 50% while optimizing query performance by up to 45%.

I partner with clinicians, operations, and business stakeholders to translate data into actionable insights, mentor teams on big-data best practices, and maintain reproducible, auditable ML lifecycles to ensure compliant, high-impact deployments.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Scientist/Engineer

Current

Athenahealth Inc

Dec 2023 - Present (1 year 9 months)

Engineered real-time streaming architectures using Spark Streaming and Kafka, reducing fraud detection and anomaly monitoring latency to sub-second levels. Optimized Redshift and Snowflake models to increase query speeds up to 45% and automated ML retraining pipelines to cut manual intervention by 70%.

Apache Spark Kafka Snowflake Databricks Airflow Terraform Python TensorFlow

Data Engineer

American Airlines

Nov 2020 - Nov 2023 (3 years)

Built streaming pipelines with Spark Streaming and Kafka on GCP Pub/Sub and AWS MSK to enable sub-second flight delay prediction and baggage tracking. Optimized Redshift and BigQuery data models to boost query performance up to 45% and migrated MapReduce workflows to Spark, reducing processing time by 55%.

Apache Spark Kafka BigQuery AWS RedShift Airflow Terraform Kubernetes Python

ETL Developer

Procter & Gamble

Jan 2019 - Oct 2020 (1 year 9 months)

Engineered reusable Spark ingestion wrappers and tuned jobs to cut onboarding time for new datasets by 30% and reduce ETL runtimes. Migrated enterprise datasets to Azure Data Lake and implemented CI pipelines to improve deployment reliability and SLA compliance.