Step inside the preparation frameworks used by FAANG+ data engineers to crack modern interview format, from SQL and data modeling to system design and optimization.
Understand how 2025 interviews have evolved and what top companies now prioritize in data engineering candidates.
Learn how to showcase both detailed technical depth and broad architectural thinking that FAANG panels look for.
Discover a step-by-step prep structure for technical, scenario-based, and cross-functional interview rounds.
Hear practical lessons from a Microsoft Data Engineer who’s guided peers through FAANG interview journeys and success stories.
At Amazon: Drives large-scale analytics using AWS, from Redshift to EMR, turning data into decisions that power global operations.
FAANG Data Expertise: 6+ years building scalable pipelines, optimizing data lakes, and solving complex engineering challenges across domains.
Mentor & Coach: Known for helping engineers break into FAANG roles through practical prep frameworks and insider guidance.
Real-World Perspective: Brings firsthand insights from inside Amazon’s data ecosystem, what top teams look for, and how to stand out in 2025.
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Join a free live session with Jinal Mehta, Data Engineer II at Amazon, as she breaks down how FAANG+ companies assess data talent in 2025. Learn what interviewers test, how top engineers prepare, and what truly sets successful candidates apart.
Inside look at how FAANG+ data interviews have evolved
Key skills that matter most from SQL to system design
Proven prep frameworks to stand out in every round
Live Q&A with an Amazon Data Engineer on cracking FAANG interviews
📅 November 14th | 🕓 04:30 – 06:00 PM PST
Jinal Mehta: Data Engineer II @ Amazon | Speaker | FAANG Interview Coach and Mentor
Inside the FAANG Interview: See how data interviews have evolved and what’s tested in 2025.
The Skill Edge: Learn what separates standout engineers in SQL, design, and scale.
The Prep Formula: Build a focused plan for coding, analytics, and architecture rounds.
Live Q&A with Jinal: Hear real insights from an Amazon Data Engineer who’s been there.
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