Senior Data Engineer with 6+ years architecting enterprise-scale cloud data platforms across banking,
healthcare, and retail. Deep expertise in Azure Databricks lakehouse architecture, real-time streaming,
and regulatory…
Senior Data Engineer with 6+ years architecting enterprise-scale cloud data platforms across banking,
healthcare, and retail. Deep expertise in Azure Databricks lakehouse architecture, real-time streaming,
and regulatory-compliant infrastructure (PCI-DSS, HIPAA, SOC 2). Proven track record processing 4B+
daily transactions, cutting cloud costs by 40%, and delivering 99.7% SLA across mission-critical
pipelines. Skilled in PySpark, Delta Lake, dbt, Kafka, and modern data stack tooling.
Architected Azure Databricks Medallion lakehouse across retail, commercial, and wealth lines.
Cut data latency from 24 hrs to under 15 min.
Built 120+ PySpark and ADF pipelines integrating 25 source systems (core banking, CRM, trading).
Sustained 99.7% SLA across 38 downstream consumers.
Delivered PCI-DSS tokenization framework using Azure Key Vault and column-level encryption.
Achieved zero audit findings in 2023 and 2024.
Automated DFAST regulatory reporting for Federal Reserve stress testing.
Reduced report prep from 5 days to 4 hours.
Adopted Delta Lake ACID and time-travel features.
Cut Finance reconciliation effort by 70%.
Optimized Spark execution plans and cluster configs.
Drove 40% cost reduction ($280K/yr) with 55% higher throughput.
Introduced dbt transformation layer.
Raised SQL test coverage from 12% to 85%.
Mentored 3 junior engineers.
Architected lakehouse processing 4.2B daily transactions and drove $280K/year in cloud cost savings., Architected Azure Databricks Medallion lakehouse across retail, commercial, and wealth lines — cut data latency from 24 hrs to under 15 min., Built 120+ PySpark and ADF pipelines integrating 25 source systems (core banking, CRM, trading); sustained 99.7% SLA across 38 downstream consumers., Delivered PCI-DSS tokenization framework using Azure Key Vault and column-level encryption — zero audit findings in 2023 and 2024., Automated DFAST regulatory reporting for Federal Reserve stress testing — reduced report prep from 5 days to 4 hours., Adopted Delta Lake ACID and time-travel features — cut Finance reconciliation effort by 70%., Optimized Spark execution plans and cluster configs — drove 40% cost reduction ($280K/yr) with 55% higher throughput., Introduced dbt transformation layer and raised SQL test coverage from 12% to 85%; mentored 3 junior engineers.
Engineered HIPAA-compliant pipelines processing 850M+ medical claims annually from 300+ payer and provider partners into Azure Synapse for population health analytics.
Built real-time member eligibility platform on Event Hubs and Stream Analytics.
Handled 120K events/sec.
Reduced eligibility errors by 34%.
Implemented Data Vault 2.0 enterprise claims warehouse with full historization.
Passed all bi-annual CMS compliance reviews.
Developed PHI de-identification pipeline (HIPAA Safe Harbor) on Databricks.
Enabled secure data sharing with external research partners.
Productionized 8 ML models for fraud detection and readmission risk using PySpark feature engineering.
Served 2M+ members.
Delivered HIPAA-compliant pipelines processing 850M+ claims/year and cut pipeline runtime by 52%., Engineered HIPAA-compliant pipelines processing 850M+ medical claims annually from 300+ payer and provider partners into Azure Synapse for population health analytics., Built real-time member eligibility platform on Event Hubs and Stream Analytics — handled 120K events/sec and reduced eligibility errors by 34%., Implemented Data Vault 2.0 enterprise claims warehouse with full historization — passed all bi-annual CMS compliance reviews., Developed PHI de-identification pipeline (HIPAA Safe Harbor) on Databricks — enabled secure data sharing with external research partners., Productionized 8 ML models for fraud detection and readmission risk using PySpark feature engineering — served 2M+ members.
Led on-premises to ADLS Gen2 migration of retail sales, inventory, and supply chain data via Azure Data Factory.
Built PySpark ETL pipelines integrating data from 80+ store systems, e-commerce platforms, and third-party logistics partners to power omnichannel analytics.
Developed 200-rule automated data quality framework (completeness, accuracy, referential integrity).
Cut downstream reporting errors by 45% across merchandising teams.
Delivered self-service analytics layer on Azure Synapse for category managers and supply chain analysts.
Reduced ad-hoc data requests to engineering by 60%.
Designed star-schema dimensional model for sales, inventory, and pricing analytics supporting 5,000+ store locations and 100M+ weekly transactions.
Migrated 15 TB of retail data to Azure 3 weeks ahead of schedule, supporting 5,000+ stores., Led on-premises to ADLS Gen2 migration of retail sales, inventory, and supply chain data via Azure Data Factory., Built PySpark ETL pipelines integrating data from 80+ store systems, e-commerce platforms, and third-party logistics partners to power omnichannel analytics., Developed 200-rule automated data quality framework (completeness, accuracy, referential integrity); cut downstream reporting errors by 45% across merchandising teams., Delivered self-service analytics layer on Azure Synapse for category managers and supply chain analysts — reduced ad-hoc data requests to engineering by 60%., Designed star-schema dimensional model for sales, inventory, and pricing analytics supporting 5,000+ store locations and 100M+ weekly transactions.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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