B

Bria Yasir

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Florida, United States

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Jobs verified_user 0% verified
  • Contour Software
    Data Engineer Lead
    Contour Software
    Mar 2022 - Current (4 years 5 months)
    • Architected enterprise-grade multi-cloud platforms leveraging Azure, GCP, and Databricks for healthcare clients handling sensitive clinical and operational datasets. • Orchestrated a full-scale lakehouse ecosystem integrating Delta Lake with Snowflake to support BI, AI, and application workloads across unified data layers. • Operationalized dbt for transformation lifecycle management and standardized Airflow-based orchestration across 100+ production pipelines. • Enforced governance frameworks with Apache Atlas to ensure data lineage, regulatory compliance, and controlled access for HIPAA-driven use cases. • Partnered with data science teams to deploy ML models into production environments, powering disease risk prediction, patient s
  • VentureDive
    Cloud Data Engineer
    VentureDive
    Aug 2018 - Feb 2022 (3 years 7 months)
    • Transitioned legacy ETL into Azure Data Factory pipelines, enabling scalable, event-driven workflows across multiple domains. • Engineered Azure Data Lake Gen2 and Databricks pipelines supporting hybrid batch and streaming for patient data. • Structured Delta Lake layers (Bronze, Silver, Gold) to deliver curated, governed, and reusable datasets. • Automated deployments with Terraform and Azure DevOps, embedding CI/CD and validated Spark applications for production reliability. • Accelerated BI adoption by integrating Snowflake, reducing query latency by 55% and enhancing analytical efficiency. • Strengthened data quality using Great Expectations, proactively resolving schema drift and data anomalies. • Delivered production-grade dat
  • NorthBay Solutions
    Big Data Specialist
    NorthBay Solutions
    Jan 2016 - Jul 2018 (2 years 7 months)
    • Built scalable batch pipelines with Apache Spark and Hive to process structured and unstructured healthcare data. • Implemented real-time ingestion using Kafka for patient monitoring sensors and medical device streams. • Improved job runtimes by 45% through optimized joins, partitioning, and caching strategies. • Consolidated datasets from EHR, lab systems, and insurance claims into a centralized Hadoop-based platform. • Produced engineered time-series datasets enabling predictive models for clinical readmission risk. • Created reusable libraries for data cleansing and anomaly detection, improving maintainability and reusability across teams.
  • CodeNinja
    Data Engineer
    CodeNinja
    Jul 2014 - Dec 2015 (1 year 6 months)
    • Automated ingestion pipelines using Talend, SQL Server, and Python to consolidate patient data across hospital systems. • Standardized clinical records and diagnosis datasets into unified models supporting compliance and reporting. • Reduced manual refresh effort by 60% through scheduled ETL workflows and automated validations. • Implemented rigorous quality checks ensuring integrity and reliability of downstream analytics. • Designed dimensional data marts supporting KPIs and executive dashboards for hospital management. • Optimized complex SQL queries for high-performance dashboards used in operational reporting.
Education verified_user 0% verified
  • B
    Bachelor of Science
Projects (professional or personal) verified_user 0% verified
  • H
    Healthcare Data Lakehouse Modernization
    Migrated on-premise ETL workflows into a Databricks and Snowflake-based lakehouse using Delta Lake and dbt, structured with Bronze-Silver-Gold layers. Enforced governance with Apache Atlas and role-based security to ensure HIPAA compliance, while enabling real-time patient data insights and predictive analytics.
  • C
    Cloud ETL Pipeline Modernization
    Replaced legacy batch jobs with modular pipelines using Talend, Python, and Airflow orchestrations. Enhanced reliability with data validation (Great Expectations) and introduced observability and monitoring, cutting failure recovery time by 50% and improving pipeline resilience.
  • P
    Predictive Patient Readmission Modeling
    Engineered ML-ready time-series datasets using Spark, Databricks, and Delta Lake for patient outcome prediction. Collaborated with data scientists leveraging Scikit-learn and MLflow to deploy models that improved readmission risk identification and early intervention planning.
  • E
    Enterprise BI & Analytics Platform
    Developed centralized data marts and semantic layers in Snowflake using dbt and automated ingestion pipelines with Airflow. Delivered KPIs through Power BI and Looker dashboards, improving self-service analytics and reducing reporting cycles by 40%.
  • R
    Real-Time Financial Fraud Detection
    Built streaming pipelines with Kafka, Spark Streaming, and AWS Lambda integrated with S3-based alerting. Reduced detection latency by 60% and automated fraud risk workflows, empowering compliance teams with near real-time monitoring and proactive interventions.