Open to opportunities

Naya R

@nayar

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Lead Data Engineer specializing in cloud, real-time analytics, and data platforms.

United States

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What I'm looking for

I seek a senior engineering role building scalable cloud-native data platforms with strong team leadership, CI/CD, and real-time analytics focus.

I am a Lead Data Engineer with 9+ years building and scaling enterprise data platforms across AWS, Azure, GCP, and Snowflake.

I architect and optimize ETL/ELT and streaming pipelines using Spark, Kafka, Flink, dbt, Airflow, and Delta Lake, and I implement lakehouse and data-mesh patterns to enable real-time analytics and AI initiatives.

I lead and mentor data engineering teams, drive CI/CD and Infrastructure-as-Code with Terraform and Azure DevOps, and apply observability and cost-optimization practices to meet SLAs while reducing cloud spend.

My track record includes large-scale migrations, production ML lifecycle automation with MLflow, and delivering measurable outcomes such as reduced release times, lower compute costs, and improved data reliability.

Experience

Work history, roles, and key accomplishments

Current

Lead Data Engineer

Current

Sepsis Scout

Apr 2021 - Present (4 years 5 months)

Architected an Azure Databricks lakehouse with Delta Lake and built Spark+Kafka streaming and batch pipelines processing 500K+ daily records; implemented DLT and MLflow and cut infra setup and release times by 50% while reducing compute costs by 25%.

Databricks Delta Lake Spark Kafka Terraform Azure DevOps MLFlow Cost Optimization

Senior Data Engineer

ZeroDown

Aug 2018 - Mar 2021 (2 years 7 months)

Designed real-time Kafka+Spark pipelines and AWS data lake (S3+Glue+Redshift Spectrum) feeding Snowflake and dbt models; created self-serve dashboards reducing manual reporting time by 60% and implemented monitoring for SLA compliance.

Kafka Spark Snowflake AWS S3 Glue Redshift DBT Tableau Observability

Data Engineer

MentalHappy

Mar 2015 - Jul 2018 (3 years 4 months)

Built Talend/NiFi batch ETL pipelines ingesting EHR, claims, and CRM data and migrated workloads to Snowflake; developed Python ETL with unit tests and Airflow orchestration, reducing data errors by 40%.