Webinar

Women in Data: Building Technical Expertise and Career Pathways in Data Engineering

Join Our Upcoming Event

Details

Date:
April 30, 2025
Time:
11:00 AM EST, 08:30 PM [IST]
Duration:
60 mins

Summary

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.

✅ 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

Hosted By

Harsha Kalbalia

[Moderator] GTM & Founding Member @ Datazip

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.

Jyoti

Senior Data Engineer @ Pharma MNC

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

Riya Khandelwal

Senior Data Engineer @ KPMG

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

Aditi Fatwani

Data Engineer @ Evernorth, Cigna Group

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

Tulsi Thakur

Data Engineer @ Amazon

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

Mitali Gupta

Business Systems @ Eczachly Inc

At EcZachly Inc, Mitali is the jack-of-all-trades, mastering the art of systems admin, dabbling in marketing strategies and project development

Summary

This 60-minute OLake panel brings together six accomplished women data engineers from healthcare, retail, cloud platforms, and large-scale enterprise systems to dissect the technical challenges behind modern data pipelines. They will cover everything from multi-terabyte CDC architectures and real-time analytics to cloud-native cost optimization, showing how sound engineering choices drive tangible business outcomes.

Chapters & Topics

Welcome and Session Overview

Moderator introduces the six panelists, outlines the focus on deep technical practices rather than high-level theory, and sets expectations for a fast-paced, Q&A-heavy hour.

Domain-Specific Pipelines

Panelists walk through specialized solutions: HIPAA-compliant clinical-trial ingestion, sub-second retail clickstream analytics, and cloud-agnostic data platforms on AWS, GCP, and Azure.

Performance Engineering Wins

Concrete examples of moving ETL from batch to streaming, shaving hours off jobs, and designing low-latency CDC paths that scale to petabytes.

Engineer’s Technical Toolkit

Progression from SQL and Python foundations to distributed-systems design, with opinions on when to generalize versus specialize in areas like Spark, Databricks, or Apache Iceberg.

Business Impact of Technical Choices

How storage-format decisions, cloud-migration tactics, and real-time architectures translate into cost savings, faster feature delivery, and measurable revenue gains.

Audience Q&A and Closing Thoughts

Live questions on tooling trade-offs, career pathways, and the future of data engineering; panelists share actionable next steps for attendees.

Action Items

Organizers to share session recording and slide deck with registrants after the event.

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