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Azran Mehrosh

@azranmehrosh

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Senior Data Engineer building scalable lakehouse platforms, streaming pipelines, and cost-efficient analytics.

United States

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What I'm looking for

I’m looking for a Senior Data Engineering role where I can lead lakehouse and streaming initiatives, optimize cost and performance, and build reliable, governed data pipelines that power analytics, AI workflows, and production-grade automation.

I’m a Senior Data Engineer with 10 years of experience designing scalable data platforms, streaming pipelines, and cloud-based analytics solutions across healthcare, SaaS, and enterprise environments. I build lakehouse architectures with Databricks, Delta Lake, and Spark Structured Streaming, focusing on performance optimization, reliability, and cost efficiency.

Across my roles, I’ve led ingestion and transformation at massive scale, implemented CI/CD automation with Terraform and GitHub Actions, and delivered real-time processing using Kafka and debuggable orchestration. I also support AI-driven data workflows—vector search, RAG pipelines, semantic retrieval systems, and LLM-ready architectures—while strengthening governance, data quality, and observability through frameworks like Great Expectations and Unity Catalog.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Oznolo

Apr 2022 - Present (4 years 2 months)

Led enterprise data platform initiatives supporting analytics and AI workloads, building a Databricks lakehouse with Delta Lake and Structured Streaming. Scaled ingestion to handle 850M+ daily records with near real-time processing and improved compute cost efficiency through Spark/Delta performance optimizations.

Databricks Delta Lake Apache Spark Pyspark DBT Kafka AWS Terraform

Senior Data Engineer

HealthBridge Analytics

Jan 2019 - Mar 2022 (3 years 2 months)

Built HIPAA-compliant healthcare data pipelines using Spark, Hive, Airflow, and AWS to support patient analytics and operational reporting. Migrated reporting from on-prem to AWS Redshift and S3 and improved reliability with reconciliation, observability, and SLA-based alerting.

Apache Spark Apache Hive Apache Airflow AWS RedShift Amazon S3 Observability

Data Engineer

Nexora Data Systems

Aug 2016 - Dec 2018 (2 years 4 months)

Developed scalable ETL and streaming pipelines using Spark, Kafka, Python, and AWS, including metadata-driven ingestion for analytics and machine learning workflows. Implemented Kafka + Debezium CDC, replaced legacy scheduling with Airflow, and optimized Spark jobs and storage to improve pipeline and query performance.

Apache Spark Apache Kafka Python Apache Airflow AWS PostgreSQL Amazon Redshift