Open to opportunities

Muhammad Iqbal

@muhammadiqbal5

Message

Staff Data Engineer specializing in cloud-native big data platforms and pipelines.

United States

Message

What I'm looking for

I seek roles building scalable, secure cloud-native data platforms where I can lead modernization, ensure compliance, and improve observability and pipeline performance.

I am a Staff Data Engineer with 10+ years building and optimizing large-scale data platforms across cloud and hybrid environments. I specialize in ETL/ELT pipeline development, big data processing, and cloud-native architectures on AWS, Azure, and GCP.

I have led teams and technical initiatives across Healthcare, SaaS, and FinTech domains, modernizing infrastructure with Terraform and Ansible and delivering high-availability systems (99.9%+ uptime). My work emphasizes data governance, compliance (HIPAA, GDPR, SOC 2, GxP), and measurable operational improvements.

I've driven pipeline performance gains—reducing processing times by up to 50% and deployment/setup times by ~70%—and implemented observability and data-quality frameworks that cut MTTR by ~40% and improved PHI accuracy. I pair hands-on engineering with cross-functional partnership to translate clinical and business needs into reliable data solutions.

I hold cloud and data engineering certifications (AWS Data Analytics, Azure Data Engineer) and a Bachelor's in Computer Science, and I am focused on building scalable, secure, and compliant data platforms that enable analytics, research, and product growth.

Experience

Work history, roles, and key accomplishments

Current

Staff Data Engineer

Current

Health Tap

Jan 2024 - Present (1 year 8 months)

Designed and scaled ETL/ELT pipelines with Spark, Airflow, SQL, and dbt, reducing processing time by 50% and enabling real-time clinical insights while ensuring 99.95% uptime for patient data workloads.

Spark Airflow DBT Kubernetes Terraform AWS Data Governance Prometheus Grafana

Senior Data Engineer

Ascend.io

May 2019 - Dec 2023 (4 years 7 months)

Built AI-native scalable data pipelines with Ascend, Airflow, and dbt, cutting data processing time by 40% and maintaining 99.9% uptime across Snowflake, BigQuery, and Databricks architectures.

Airflow DBT Spark Terraform Snowflake BigQuery Databricks Prometheus

Data Engineer

XpertDox

Nov 2015 - Mar 2019 (3 years 4 months)

Designed and maintained scalable ETL pipelines and optimized AWS infrastructure, implemented containerized deployments and monitoring solutions to improve reliability and operational efficiency.