Hamza Khal

Senior Data Engineer with 8+ years of experience building and scaling data platforms across fintech, healthcare, SaaS, telecom, and energy domains. Hands-on expertise in Databricks, Spark, Kafka, Snowflake, and AWS for large-scale batch and streaming workloads. Experienced in cloud migrations, lakehouse architectures, and distributed systems processing billions of events daily. Strong track record of improving platform reliability, performance, and infrastructure efficiency.

Senior Data Engineer – Cloud Data & Streaming Systems - Consensus

(2024-06)

• Designed and implemented a multi-region AWS and Azure lakehouse platform processing 8B+ financial transactions and IoT events daily.
• Built Kafka and Flink based streaming pipelines enabling sub-second fraud detection for real-time workloads.
• Led migration of on-prem Hadoop workloads to Databricks Lakehouse, reducing annual infrastructure costs by $1.4M.
• Engineered disaster recovery framework achieving 99.99% SLA across mission-critical workloads.
• Implemented data mesh governance across 14 domains improving ownership and compliance.
• Optimized Spark workloads and query execution strategies, improving processing performance by 60%.
• Enabled self-service analytics for 200+ analysts and ML engineers.

Data Engineer – Big Data Telecom Analytics - CorroHealth

(2021-10 - 2024-04)

• Built HIPAA-compliant data ingestion pipelines integrating HL7 and FHIR streams processing over 2TB+ of data daily.
• Developed scalable ELT pipelines in Snowflake and Spark for predictive analytics.
• Developed CDC pipelines using Kafka and Debezium to support near real-time analytics and reporting.
• Reduced Snowflake compute cost by 35% through optimization strategies.
• Implemented automated data validation improving reliability and compliance.

Junior Data Engineer – Data Warehousing - Sikich

(2017-11 - 2021-08)

• Developed Hadoop ETL pipelines processing 4B+ telecom records daily.
• Designed churn analytics data marts improving retention modeling.
• Implemented Kafka-based ingestion pipelines, reducing batch processing latency by 8 hours.
• Improved Hive strategies improving query performance by 40%.

Associate Data Engineer – SQL & Data Modeling - Calendly

(2016-01 - 2017-09)

• Developed SSIS and Informatica workflows supporting enterprise reporting.
• Designed dimensional models and PL/SQL procedures for financial systems.
• Automated Unix batch workflows, improving scheduling reliability and reducing operational overhead.

Bachelor of Science - Computer Science - University of the Punjab (2011 - 2015)