Tariq Farooq

Principal/Lead Data Engineering Architect with 10+ years of experience specializing in the design, development, and scaling of distributed, cloud-native data platforms for Fintech/Financial (Regulated), Healthcare (CMS/HIPAA), and AI/ML environments. Expert in architecting real-time streaming (Kafka, Spark Streaming, Flink) and batch ETL/ELT pipelines using Spark/PySpark, Airflow, dbt, and NiFi. Highly proficient in Python (Flask) and Advanced SQL. Deep expertise across AWS, Azure, and GCP, specializing in modern data stacks including Redshift, Snowflake, BigQuery, and Delta Lake/Lakehouse architectures using dimensional modeling. Proven ability to define and execute end-to-end data engineering strategy, from secure ingestion and data quality validation (Great Expectations) to performance-optimized modeling, enabling scalable, high-quality, and analytics-ready data assets. Strong background in MLOps (MLflow, Feature Stores, Kubeflow), Infrastructure-as-Code (Terraform, Kubernetes), CI/CD (Azure DevOps, Jenkins, GitLab), and ensuring compliance (HIPAA, GDPR, SOX) and data lineage. Proven track record of performance optimization, reducing processing time by 40% and accelerating insights by 30% while mentoring teams and driving enterprise-wide data maturity.