I am a Senior Data Engineer with 6+ years of experience building and scaling data platforms and ML pipelines across AWS, Azure, and GCP. I design end-to-end data architectures—from ingestion and ETL/ELT to data modeling and real-time streaming—and I specialize in cloud-native lakehouse solutions (Redshift, BigQuery, Snowflake, Delta Lake, Iceberg). My work emphasizes MLOps automation, including feature engineering, model training and deployment, drift monitoring, and automated retraining using AWS SageMaker, MLflow, Databricks ML, and Snowflake Snowpark. I enjoy delivering production-grade solutions with Python, SQL, dbt, Kafka, and CI/CD, driving faster analytics, reliable deployments, and governance compliant with HIPAA, GDPR, and HITRUST.

Brinda Sharma

I am a Senior Data Engineer with 6+ years of experience building and scaling data platforms and ML pipelines across AWS, Azure, and GCP. I design end-to-end data architectures—from ingestion and ETL/ELT to data modeling and real-time streaming—and I specialize in cloud-native lakehouse solutions (Redshift, BigQuery, Snowflake, Delta Lake, Iceberg). My work emphasizes MLOps automation, including feature engineering, model training and deployment, drift monitoring, and automated retraining using AWS SageMaker, MLflow, Databricks ML, and Snowflake Snowpark. I enjoy delivering production-grade solutions with Python, SQL, dbt, Kafka, and CI/CD, driving faster analytics, reliable deployments, and governance compliant with HIPAA, GDPR, and HITRUST.

Available to hire

I am a Senior Data Engineer with 6+ years of experience building and scaling data platforms and ML pipelines across AWS, Azure, and GCP. I design end-to-end data architectures—from ingestion and ETL/ELT to data modeling and real-time streaming—and I specialize in cloud-native lakehouse solutions (Redshift, BigQuery, Snowflake, Delta Lake, Iceberg).

My work emphasizes MLOps automation, including feature engineering, model training and deployment, drift monitoring, and automated retraining using AWS SageMaker, MLflow, Databricks ML, and Snowflake Snowpark. I enjoy delivering production-grade solutions with Python, SQL, dbt, Kafka, and CI/CD, driving faster analytics, reliable deployments, and governance compliant with HIPAA, GDPR, and HITRUST.

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Experience Level

Expert
Expert
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Expert
Expert
Expert
Expert
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Work Experience

Senior Data Engineer at Cardinal Health
June 1, 2023 - Present
Led modernization of healthcare analytics by building a HIPAA-compliant Lakehouse on AWS using Glue, EMR (Spark), and Redshift. Integrated EHR, claims, HL7/FHIR, and DICOM imaging data to support real-time ML-driven patient monitoring and predictive risk analytics across clinical, financial, and operations domains. Architected real-time streaming pipelines with Amazon Kinesis Data Streams, Kafka, and EMR Structured Streaming to process over 1M HL7/FHIR events per second with sub-500ms latency. Built feature store schemas in Amazon RDS (PostgreSQL/MySQL) aligned with FHIR, HL7, and DICOM standards, enabling seamless data exchange between Redshift, Delta Lake on S3, and on-prem systems. Achieved 99.99% uptime by deploying containerized ML pipelines on Amazon EKS with CI/CD, supporting horizontal scaling for peak traffic and retraining workloads. Implemented Snowflake data marts with 200+ modular dbt transformations, schema testing, and lineage, improving data quality and reducing reporti
Data Analytics Engineer at Lockheed Martin
January 1, 2022 - April 1, 2023
Contributed to a multi-cloud data platform across AWS, Azure, and GCP, unifying telemetry, mission, and supply chain data. Delivered real-time analytics pipelines with Kafka, Spark, and Snowflake to enable mission readiness dashboards and predictive maintenance models. Engineered large-scale data transformations with PySpark, delivering analytics-ready datasets into Redshift, Synapse, and BigQuery with schema-on-read. Implemented multi-cloud metadata and lineage using AWS Glue Catalog, Lake Formation, and Azure Purview; established robust monitoring and alerting across CloudWatch, Azure Monitor, and custom metrics. Built CI/CD with Azure DevOps, Terraform, CodePipeline, and Git to automate deployments of Glue Jobs, dbt models, and container images.
ETL Developer at Candid Health
March 1, 2019 - December 1, 2021
Developed and maintained complex ETL workflows using Informatica PowerCenter to process clinical and insurance data from Oracle and SQL Server into centralized data warehouses. Enhanced reliability of nightly loads with optimized SSIS packages, batch control frameworks, and data cleansing procedures. Implemented HIPAA-compliant access controls and encryption, collaborated in Agile sprints, and produced documentation for lineage and deployment guidelines.

Education

Masters of Computer Science at Lincoln International College
January 11, 2030 - January 10, 2026

Qualifications

Google Professional Data Engineer
January 11, 2030 - January 10, 2026
Snowflake SnowPro Core
January 11, 2030 - January 10, 2026
AWS Solutions Architect – Professional
January 11, 2030 - January 10, 2026

Industry Experience

Healthcare, Life Sciences, Financial Services, Professional Services, Software & Internet