M

Muhammad Iqbal

About

Detail

United States

Contact Muhammad regarding: 
Flexible work

Timeline


work
Job
school
Education

Résumé


Jobs verified_user 0% verified
  • Validic
    Lead Data Engineer
    Validic
    Sep 2022 - Current (4 years 2 months)
    Designed and led the development of scalable, compliant data platforms on AWS and Azure that power patient analytics and clinical intelligence. Directed the creation of robust ETL and ELT pipelines with Spark, Airflow, and dbt, enabling near real-time delivery of critical healthcare insights. Automated infrastructure provisioning through Terraform and Ansible, cutting deployment time and ensuring consistency across multiple environments. Built unified monitoring and observability using Prometheus, Grafana, ELK, and Datadog, improving reliability and accelerating incident resolution. Drove data quality and governance programs to maintain accuracy, lineage, and regulatory compliance under GDPR and healthcare standards. Collaborated with produ
  • Ascend.io
    Senior Data Engineer
    Ascend.io
    Feb 2019 - Jun 2022 (3 years 5 months)
    Designed and delivered scalable, high-performance data pipelines using Spark, Databricks, Airflow, and dbt across AWS, GCP, and Azure environments. Architected a modern data lakehouse integrating Snowflake, BigQuery, and Delta Lake, improving query speed, scalability, and cost efficiency. Automated infrastructure with Terraform and CI/CD pipelines, ensuring consistent deployments and reducing delivery time by more than 40%. Introduced observability frameworks with SLOs, DAG SLAs, and data quality metrics, improving reliability and cutting pipeline failures significantly. Partnered with product, analytics, and ML teams to design data models that powered AI-driven insights and customer-facing dashboards. Implemented data governance and access
  • XpertDox
    Data Engineer
    XpertDox
    Nov 2015 - Dec 2018 (3 years 2 months)
    Built and maintained ETL pipelines to integrate diverse healthcare datasets into AWS using S3, RDS, and Lambda for downstream analytics. Migrated legacy systems to a cloud-first data warehouse, improving reporting speed and reliability for clinical and operational users. Implemented Docker and Kubernetes for workload containerization, improving deployment consistency and system scalability. Created monitoring dashboards with Prometheus and ELK to track data pipeline performance and proactively detect anomalies. Automated infrastructure provisioning with Terraform and CloudFormation, reducing manual setup and accelerating delivery cycles. Collaborated with clinical teams to develop HIPAA-compliant analytics pipelines supporting patient engag
Education verified_user 0% verified
  • C
    Certified Health Data Analyst
    Feb 2015 - Apr 2015 (3 months)
  • A
    AWS Certified Data Analytics
    May 2015 - Jul 2015 (3 months)
  • C
    Cloud Professional Data Engineer
    Aug 2015 - Oct 2015 (3 months)
  • B
    Bachelor's of Sciences
    Feb 2011 - Aug 2015 (4 years 7 months)