Open to opportunities

Muh Mubeen Ashraf

@muhmubeenashraf

Senior data solution architect who builds cloud-native ETL, lakehouse, and real-time analytics systems that cut cost and performance.

United States

Message

What I'm looking for

I’m looking to architect and lead cloud-native data platforms—lakehouse, ETL/ELT, and real-time streaming—where strong governance and CI/CD matter, and where I can drive measurable cost and performance improvements.

I’m a Senior Data Solution Architect with 11+ years of experience designing and delivering scalable, cloud-native data platforms and real-time analytics solutions across AWS, Azure, and GCP. I specialize in Lakehouse architectures, ETL/ELT pipelines, and event-driven systems.

I’ve led initiatives that reduce infrastructure costs by up to 50% and improve data performance by 40% through optimized architectures. At Monte Carlo, I architected real-time streaming infrastructures using Apache Kafka, Apache Flink, and AWS Kinesis—enabling 99.9% uptime and improving operational responsiveness by 35%.

I build AI/ML-ready data ecosystems by integrating governance, lineage, and feature-ready datasets. I’ve established enterprise-wide data governance policies ensuring 100% compliance with GDPR and HIPAA, and I’ve enabled model deployment workflows using MLflow and feature engineering.

I also focus on modern platform experiences—Microsoft Fabric, Databricks, and unified lakehouse processing—so analytics teams can move faster without breaking reliability. Whether migrating legacy warehouses to cloud or mentoring cross-functional teams, I bring strong CI/CD, infrastructure-as-code, and performance-tuning discipline to every delivery.

Experience

Work history, roles, and key accomplishments

Current

Data Solution Architect

Current

Monte Carlo

Oct 2022 - Present (3 years 8 months)

Architected real-time streaming infrastructures with Apache Kafka, Apache Flink, and AWS Kinesis, enabling 99.9% pipeline uptime and improving supply chain visibility and operational responsiveness by 35%. Designed cloud-native lakehouse architectures and ETL/ELT pipelines across AWS/Azure/GCP, reducing infrastructure costs by 50% and improving query performance by 40% while enforcing GDPR and HIP

Apache Kafka Apache Flink AWS Kinesis Snowflake Microsoft Fabric ETL ELT Terraform Gitlab CI

Senior Data Engineer

Cloudera

Aug 2019 - Sep 2022 (3 years 1 month)

Designed and maintained cloud-scale ELT pipelines using Spark, Snowflake, and Airflow to support analytics and reporting at scale. Built automated ingestion and transformation workflows with NiFi/Airflow, implemented data contracts aligned to Data Mesh principles, and collaborated with data science teams to deploy ML models using Databricks and MLflow.

Apache Spark Snowflake Apache Airflow Apache NiFi Databricks MLFlow Performance Tuning Gitlab CI

Data Engineer

DataArt

Jun 2017 - Jul 2019 (2 years 1 month)

Implemented healthcare data governance including data lineage, access control, and regulatory compliance. Built automated data quality validation with Great Expectations, reducing data discrepancies by 40%, and delivered faster integrations by streamlining ingestion from REST APIs, flat files, and cloud databases.

Google Cloud Platform Data Lake Great Expectations Data Validation Data Lineage REST APIs CI CD (Exposure)

ETL & Data Warehouse Engineer

Steer Health

Feb 2014 - May 2017 (3 years 3 months)

Supported healthcare-focused data platforms by integrating structured and semi-structured data while meeting regulatory and security requirements. Designed data warehouse solutions using dimensional modeling (Kimball) and built real-time analytics datasets with AWS and Google BigQuery, including dashboarding with Tableau/Power BI and compliance with HIPAA and data governance controls.