MARK FAHAD

Staff Data Engineer with over 10 years of experience designing scalable data solutions across healthcare, finance, and ecommerce sectors using modern cloud architectures on AWS, Azure, and GCP.

✨ Hey! I'm Mark Fahad. I'm a Staff Data Engineer with over 10 years of progressive experience designing and implementing scalable data solutions across healthcare, finance, ecommerce, and technology sectors. I specialize in building enterprise-grade data platforms using Databricks, Snowflake, and modern cloud architectures, transforming raw data into actionable insights that drive business intelligence and analytics.

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50 +

Production ML models deployed and maintained successfully

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45 %

Infrastructure cost reduction through AWS optimization

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10 +

Years of expertise in data engineering and architecture

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100 +

Daily ETL/ELT workflows managed with Airflow orchestration

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My Approach to Data Engineering and Technical Excellence

  • - Scalable Architecture
  • - Data Quality First
  • - Cloud Optimization
let's talk about project

Excellence

Excellence in data engineering means building robust pipelines that handle millions of events with precision. Every data transformation is optimized for performance, reliability, and maintainability at scale.

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Innovation

Leveraging cutting-edge technologies like MLOps, real-time streaming with Kafka, and LLM-powered RAG systems. Innovation drives efficiency, enabling intelligent automation and predictive analytics that transform business operations.

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Expertise

Over 10 years mastering data architecture across AWS, Azure, and GCP. Deep expertise in Databricks, Snowflake, Python, Spark, and modern data stack tools ensures enterprise-grade solutions that deliver measurable business impact.

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My Core
Technologies

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95%

Python

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93%

Spark

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92%

SQL

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90%

AWS

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88%

Databricks

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Work Experience

A proven Data Engineer with over 10
years
of expertise

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App / Development

Online Learning Platform

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App / Development

Online Learning Platform

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App / Development

Online Learning Platform

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App / Development

Online Learning Platform

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award winning

previous Work & Achievements

2010

Recognized for outstanding creativity

2015

Celebrated for business innovation

2020

Honored for customer-centric excellence

2025

Creative solutions with lasting impact
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Mark transformed our data infrastructure completely. His expertise in building scalable data pipelines and implementing MLOps best practices helped us reduce infrastructure costs by 45% while improving data quality. He's a true data engineering expert who delivers exceptional results consistently.

— Sarah Mitchell

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Working with Mark was transformative for our data team. He built our entire data lakehouse from scratch on Databricks, implemented real-time streaming pipelines, and deployed 50+ ML models to production. His technical depth and ability to architect complex systems is outstanding.

— David Chen

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Mark's expertise in healthcare data systems is exceptional. He implemented HIPAA-compliant data governance with Unity Catalog, built ETL pipelines processing millions of records daily, and created real-time analytics dashboards. His work directly improved patient care outcomes through better data insights.

— Rebecca Johnson

frequently asked questions

  • What data engineering technologies do you specialize in?
    I specialize in Python, Spark, SQL, Databricks, Snowflake, AWS, Kafka, Airflow, dbt, and MLOps tools like MLflow. I have deep expertise in building scalable data pipelines, real-time streaming, and cloud data architectures.
  • What type of projects have you worked on?
    I've built enterprise MLOps platforms, real-time fraud detection systems, Customer 360 platforms with graph analytics, and HIPAA-compliant healthcare analytics solutions. My work spans data warehousing, streaming pipelines, and ML infrastructure.
  • What's your experience with cloud platforms?
    I have 10+ years of experience across AWS, Azure, and GCP. I've architected data lakes, implemented lakehouse architectures on Databricks, built Snowflake warehouses, and deployed containerized data services on Kubernetes.
  • Do you have experience with real-time data streaming?
    Yes, I've built production systems processing millions of events daily using Kafka, Spark Streaming, and CDC tools like Debezium. I've implemented real-time fraud detection, inventory systems, and streaming analytics pipelines with sub-second latency.
  • Are you available for contract or full-time positions?
    Yes, I'm open to both contract and full-time opportunities. I'm looking for challenging data engineering roles where I can architect scalable data platforms, implement MLOps infrastructure, and lead technical initiatives.

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