Senior Cloud Data Platform Engineer

Rizwan Asghar

Senior Data Engineer — Cloud Data Platform Engineer

# ********.*******@*****.*** ï linkedin.com/in/r-asghar H 516-***-**** * New York Summary

Senior Data Engineer with 9+ years of experience designing cloud-native data platforms, Lakehouse architectures, and real-time streaming solutions across AWS and Azure. Expertise in Databricks, Spark, Kafka, Snowflake, and Airflow, building scalable pipelines processing billions of events while reducing infrastructure costs and enabling enterprise analytics and machine learning initiatives.

Technical Skills

Languages: Python, SQL, PySpark, Scala

Big Data: Apache Spark, Databricks, Delta Lake, Kafka, Flink Cloud: AWS, Azure, GCP

Data Warehousing: Snowflake, Redshift, BigQuery, Synapse Orchestration: Airflow, AWS Glue, Azure Data Factory DevOps: Terraform, Docker, Kubernetes, Azure DevOps, GitHub Actions Governance: Unity Catalog, Great Expectations, OpenMetadata AI/ML: MLflow, Feature Store, LangChain

Work Experience

Senior Data Engineer — mCards Inc. Feb 2025 – Present

• Architected a multi-region Databricks Lakehouse platform processing 18B+ financial events monthly.

• Reduced ETL latency by 72% using Delta Live Tables, Structured Streaming, and Spark optimization.

• Implemented Unity Catalog, RBAC, and lineage tracking, reducing audit preparation effort by 80%.

• Built Kafka-based fraud detection pipelines with sub-30-second processing latency.

• Reduced annual cloud infrastructure costs by $2.4M through workload optimization and autoscaling.

• Led a team of 8 Data Engineers, driving architecture standards and cloud modernization initiatives. ETL Developer / Data Engineer — iMuto Software Solutions LLC Mar 2019 – Dec 2024

• Designed enterprise Lakehouse platforms processing 3+ PB of data for Fortune 500 clients.

• Developed reusable PySpark frameworks, reducing pipeline development time by 45%.

• Improved query performance by 65% through Delta Lake optimization and Spark tuning.

• Automated cloud deployments using Terraform, Azure DevOps, and GitHub Actions.

• Built ML feature engineering pipelines supporting recommendation systems serving 100M+ users. Data Engineer — Envoy Jan 2017 – Jan 2019

• Built AWS Glue, EMR, Spark, and Redshift pipelines processing 40TB+ of data daily.

• Reduced Spark compute costs by 58% through partitioning and workload optimization.

• Developed metadata-driven ingestion frameworks adopted across engineering teams.

• Improved pipeline reliability to 99.95% through monitoring, alerting, and SLA reporting. Key Projects

Enterprise Lakehouse Modernization

• Migrated legacy Hadoop workloads to a Databricks Lakehouse using Delta Lake, Unity Catalog, and Terraform, reducing operational costs by 40%.

Real-Time Fraud Detection Platform

• Developed Kafka and Spark Structured Streaming pipelines processing millions of transactions with sub-30-second fraud detection latency.

Enterprise Machine Learning Feature Platform

• Built ML feature engineering pipelines using MLflow and Feature Store, accelerating model deployment and improving production consistency.

Education

02/2011 - 09/2015 B.S. in Computer Science, The Islamia University of Bahawalpur

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