About this event
Join us for an in-depth technical discussion with six accomplished women data engineers who are architecting the backbone of modern data-driven organizations. This 60-minute session brings together specialists from healthcare, retail, cloud platforms, and enterprise data systems to share their technical approaches to solving complex data engineering challenges.
About the session:
Our panelists bring diverse expertise across the technical spectrum - from optimizing multi-terabyte data pipelines and implementing CDC-based architectures to designing cloud-native data platforms that drive significant business outcomes. With combined experience spanning AWS, GCP, Azure, and tools like Spark, Databricks, and Apache Iceberg, they'll provide practical insights for both emerging and established data professionals.
What You'll Learn:
- Domain-Specific Technical Solutions: Discover specialized approaches for healthcare compliance pipelines, retail real-time analytics, and optimizing cloud data architectures
- Performance Engineering: Technical strategies that have achieved measurable results, including how to design systems that move from batch to real-time with minimal latency
- The Engineer's Technical Toolkit: Practical progression from foundational skills (SQL/Python) to advanced distributed systems design, with guidance on specialization vs. generalization
- Business Impact Focus: How technical decisions in data engineering directly influence organizational outcomes, cost optimization, and scalability
Featured Technical Experience:
- Our panelists have implemented solutions that delivered concrete business results, including:
- Clinical trial data pipelines that maintain regulatory compliance while enabling advanced analytics
- Multi-terabyte data processing optimizations that reduced ETL times from hours to minutes
- Cloud migration strategies that significantly reduced storage costs while improving query performance
- Real-time data architectures designed for petabyte-scale operations
Who should join?
This technical session is ideal for data engineers, architects, and technology leaders looking to enhance their understanding of modern data engineering practices and career development pathways in this rapidly evolving field.
Hosted by
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Guest speaker
Tulsi Thakur Data Engineer @ AmazonG
Results-driven professional with expertise in Python, SQL, database management, data visualization. Contributed to Redshift migration project at Amazon, saving significant AWS storage costs, focusing on optimizing storage and enhancing data processing efficiency and successfully onboarded Source-to-Sink Views pipeline.
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Guest speaker
Riya Khandelwal Senior Data Engineer @ KPMGG
Experienced Data Engineer with over 5 years of expertise in designing and developing large-scale data pipelines, ETL workflows, analytics solutions, and data warehouse architectures. She has successfully delivered multi-terabyte, scalable big data solutions for leading organizations, leveraging technologies such as Python, SQL, Spark, Databricks, and Microsoft Azure.
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Team member
Harsha Kalbalia GTM @ Datazip | Founding Member @ DatazipT
Harsha is a user-first GTM specialist at Datazip, transforming early-stage startups from zero to one. With a knack for technical market strategy and a startup enthusiast's mindset, she bridges the gap between innovative solutions and meaningful market adoption.
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Guest speaker
Mitali Gupta Business Systems @ Eczachly Inc.G
At EcZachly Inc, Mitali is the jack-of-all-trades, mastering the art of systems admin, dabbling in marketing strategies and project development.
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Guest speaker
Aditi Fatwani Data Engineer @ Evernorth, Cigna GroupG
Aditi designs systems that move and transforms data at scale, optimizes costs on the cloud, and creates real impact for businesses across healthcare, retail, and agriculture. She works primarily with AWS and tools like Glue and Spark, but what drives her every day is solving complex problems that help teams make better, faster decisions.
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Guest speaker
Jyoti . Senior Data Engineer @ Pharma MNCG
She's a Senior Data Engineer at GSK with over six years of experience in building cloud-native data platforms and delivering impact across the healthcare and life sciences domain. She brings strong domain knowledge in clinical trials and regulatory data, with hands-on experience in PII data anonymization and curation, which are crucial for compliance and data sharing in this space.
OLake by Datazip
Fastest way to replicate your data to Apache Iceberg.OLake is an open-source data ingestion tool available on GitHub, developed by Datazip, Inc. Its primary function is to replicate data from transactional databases and streaming platforms (like PostgreSQL, MySQL, MongoDB, Oracle, and Kafka) into open data lakehouse formats, like Apache Iceberg.
