Nandini B

About Nandini B

Data Engineer with over four years of hands-on experience designing and delivering scalable, production-grade data pipelines and modern lakehouse architectures across healthcare, insurance, banking, and pharmaceutical domains. Skilled in building both batch and real-time streaming solutions using PySpark, Python, SQL, and Apache Kafka, with strong expertise across AWS, Azure, and GCP ecosystems. Proven ability to develop cloud-native data platforms leveraging Snowflake, Databricks, and BigQuery while ensuring high performance, reliability, and cost optimization. Experienced in implementing robust data governance frameworks, including data lineage, quality checks, and regulatory compliance aligned with HIPAA, GDPR, SOX, and GxP standards. Adept at orchestrating workflows using Airflow and cloud-native tools, and integrating AI/ML capabilities such as feature engineering, LLM-based analytics, and generative AI use cases. Strong collaborator with a focus on delivering business-driven insights, improving data accessibility, and enabling advanced analytics at scale.

Experience

1. Data Engineer

   Meta

   Dec 2024 — Present · Lubbock, TX, US

   Designed and optimized scalable data pipelines on Databricks (PySpark, Delta Lake), reducing ETL latency by35% and enabling analytics teams to query petabyte-scale datasets efficiently. Built reusable ELT models with dbt + Snowflake, standardizing transformations and improving data qualitychecks. Automated data orchestration with Airflow (20+ DAGs), cutting operational overhead by 40%. Developed event-driven streaming pipelines using AWS Lambda + Kinesis, enabling real-time system monitoring. Partnered with analytics and ML teamsto deliver clean, production-ready data for product insights andexperimentation.Enhanced CI/CD pipelines with Jenkins + Terraform, reducing release cycle times by 50%.

Education

• Texas Tech University

  Master's Degree, Computer Science