Sai Asfar

I’m a Principal / Senior Data Engineer with 9+ years of experience designing and building scalable cloud-native data platforms across AWS, Azure, and GCP. I specialize in Apache Spark, Kafka, Flink, Snowflake, Databricks, and modern Lakehouse architectures, with a strong focus on ETL/ELT development, real-time processing, and analytics enablement.

At Neudesic, I’ve architected and delivered batch and real-time data pipelines using Apache Spark, Kafka, and Flink, improving reliability and performance at enterprise scale. I modernized legacy ecosystems by migrating to cloud Lakehouse architectures, built robust ETL/ELT frameworks with Azure Data Factory and Airflow/dbt, and enabled AI/ML-ready data foundations through close collaboration with data scientists and business stakeholders. I also established DataOps best practices using CI/CD automation and Infrastructure as Code (Terraform/CloudFormation) to increase deployment efficiency and platform stability.

Earlier at Aunalytics, I served as Senior Data Engineer / Team Lead, leading the implementation of modern data warehousing and Lakehouse solutions for analytics, predictive modeling, and reporting. I developed data quality, MDM, metadata management, and governance frameworks to create a “single source of truth,” while mentoring engineers and driving Agile delivery and code review standards. I implemented DataOps and DevOps practices (CI/CD automation, IaC, monitoring, performance optimization) to reduce deployment cycles and strengthen platform reliability.

In my prior role at Kollabio, I built scalable ETL pipelines and cloud data architectures for federal and commercial clients, delivering both real-time and batch workflows. I’ve applied these capabilities to healthcare interoperability (HL7/FHIR with HIPAA-aligned controls), IoT predictive maintenance (time-series analytics and anomaly detection), and real-time supply chain intelligence (Kafka/Spark/Flink with Lakehouse storage), always with a focus on secure, scalable, high-performance data outcomes.