Brinda Sharma

I am a Senior Data Engineer with 6+ years building and scaling data platforms and ML pipelines across AWS, Azure, and GCP. I design end-to-end data architectures including ingestion, ETL/ELT, data modeling, and real-time streaming for production analytics and ML.

My work focuses on cloud-native lakehouse solutions (Redshift, BigQuery, Snowflake, Delta Lake) and automated MLOps using SageMaker, MLflow, Databricks ML, and Snowflake Snowpark. I have delivered HIPAA- and DoD-compliant systems that support real-time patient monitoring, predictive maintenance, and mission analytics.

At Cardinal Health I led an enterprise modernization to a HIPAA-compliant lakehouse on AWS, built streaming pipelines processing over 1M HL7/FHIR events per second, and implemented IaC and CI/CD practices that reduced release errors by 70% and deployment time by 65%. At Lockheed Martin I contributed multi-cloud platforms, telemetry pipelines, and metadata/lineage frameworks enabling mission readiness dashboards and predictive models.

I mentor junior engineers, bridge clinical and technical stakeholders, and embed governance and monitoring into data products to ensure reliability, security, and fast time-to-insight. I seek roles where I can lead scalable data platform initiatives, strengthen MLOps practices, and drive measurable business impact.