Alex Ahmad
@alexahmad1
I am an enterprise data and cloud platform architect specializing in streaming and lakehouse solutions.
What I'm looking for
I am an innovative data solution architect with 12+ years designing, scaling, and optimizing cloud-native, high-volume data platforms. I focus on real-time streaming, lakehouse architecture, and data governance to deliver analytics-ready assets that drive business outcomes.
At scale, I have built platforms that process billions of daily events, integrated Snowflake and AWS services, and orchestrated hundreds of Airflow DAGs to deliver reliable, low-latency analytics. I emphasize cost efficiency and operational stability through serverless migrations and Terraform-based infrastructure as code.
I lead and mentor engineers, having directed a team of six and established agile delivery workflows and structured mentorship programs to improve delivery efficiency and code quality. I champion domain-driven data mesh approaches, data contracts, and centralized quality and lineage using Great Expectations and Apache Atlas.
I seek to partner with cross-functional teams to accelerate time-to-insight, reduce operational costs, and enable self-service analytics. I bring deep hands-on expertise across Apache Spark, Kafka, Flink, Snowflake, Airflow, AWS, and modern DevOps practices to deliver governed, scalable data platforms.
Experience
Work history, roles, and key accomplishments
Designed a real-time analytics platform processing over two billion daily events and led a team of six to deliver telemetry, personalization, and engagement tracking; migrated Hadoop workloads to a serverless AWS Lakehouse and built 300+ Airflow DAGs to publish curated Snowflake datasets.
Built Spark and Airflow pipelines and Flink streaming solutions for fraud detection and anomaly scoring, improving incident detection and enabling predictive analytics; delivered optimized Redshift and BigQuery data marts to support global reporting.
Data Engineer
Innovotech Solutions
Aug 2013 - Sep 2018 (5 years 1 month)
Engineered NiFi and Kafka ingestion workflows capturing IoT telemetry from millions of connected devices, designed Hive and HBase models for ML-driven maintenance predictions, and tuned Hadoop clusters to reduce job execution times while enforcing GDPR/HIPAA retention policies.
Education
Degrees, certifications, and relevant coursework
National University of Computer and Emerging Sciences (FAST-NUCES)
Bachelor of Science
Completed a Bachelor of Science at the National University of Computer and Emerging Sciences (FAST-NUCES).
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
Skills
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