Spark Deep Dive: Cost-Effective Strategies to Scale to Petabytes

New
·

8 Weeks

·

Cohort-based Course

Master Spark internals, optimizations & real-world scaling to crack FAANGM interviews & boost your salary by $100K+—with expert-led insights

Previously at

Amazon
Amazon Web Services
Databricks
ZS Associates

Course overview

Stand Out in Data Engineering: Master Distributed Systems


🔧 Hands-on Benchmarking & Real-World Problem Solving

Engage in industry-level assignments where you benchmark, optimize, and fine-tune Spark jobs. Tackle real-world data challenges with confidence, applying your skills to practical projects that mirror actual industry scenarios.


🎯 Crack FAANGM Interviews with a Proven Approach

Develop the skills to confidently answer tough Spark interview questions, explain complex concepts in simple terms, and structure responses the way top companies expect. Gain targeted insights and hands-on practice to increase your chances of landing top-tier FAANGM positions.


📚 Structured Learning That Builds Retention

Benefit from a progressive course structure that layers concepts for deep understanding. Unlike scattered free content, this structured approach ensures that Spark’s mechanics are thoroughly grasped and directly applicable to your professional work.


✅ Master Spark Internals & Performance Optimization

Go beyond surface-level knowledge by deeply understanding Spark’s architecture, execution model, and optimization strategies. Learn to efficiently handle and scale petabyte-scale datasets, enhancing your ability to design robust and high-performance data pipelines.


🤝 Exclusive Mentorship & Community Support

Receive direct feedback from expert instructors and engage with a strong cohort of peers. Gain access to an active learning community that fosters collaborative problem-solving and knowledge sharing, accelerating your growth and professional development.


🔧 Learn how to decipher the Spark UI

Spark UI contains extensive information and can be overwhelming for the average user. Based on my 10 years of experience with Spark UI, I will guide you on what to focus on and what truly matters.

Who is this course for

01

Data Engineers proficient in SQL and Python but new to distributed systems.

02

Engineers who have used Spark but haven't worked with it on large projects, knowing the basics but not how it works behind the scenes

03

If you're struggling with technical interviews, especially system design or Spark-related questions.


Or


Planning to get into FAANGM

What you’ll get out of this course

Deep Understanding of Spark Internals & Performance Optimization

  • Go beyond API calls—learn how Spark actually works under the hood.
  • Master shuffling, partitioning, and query execution to handle petabyte-scale data efficiently.


Hands-on Projects & Real-World Benchmarking

  • Optimize real Spark jobs by tuning shuffle partitions, hardware configurations, and join hints.
  • Benchmark write speed and query performance across different table formats, including Liquid Clustering and Z-Ordering.

Interview Prep for FAANGM & System Design Rounds

  • Learn how to explain complex Spark concepts simply, a key skill for FAANGM interviews.
  • Tackle real Spark interview questions and data modeling scenarios to stand out in technical rounds.

Career Growth & Industry Best Practices

  • Gain insights from someone who has built and optimized Spark at Amazon, AWS, and Databricks.
  • Learn how to create job opportunities, crack interviews, and position yourself for high-paying roles.

This course includes

8 interactive live sessions

Lifetime access to course materials

1 in-depth lesson

Direct access to instructor

6 projects to apply learnings

Guided feedback & reflection

Private community of peers

Course certificate upon completion

Maven Satisfaction Guarantee

This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.

Course syllabus

Week 1

Mar 18—Mar 23

    David vs. Goliath: When a Tiny Spark Cluster Wrestles a 100 GB dataset

    • Mar

      19

      Master Spark's Core Concepts & Architecture

      Wed 3/1911:00 PM—12:30 AM (UTC)
    2 more items • Free preview

Week 2

Mar 24—Mar 30

    Every day I'm shuffling!!!! - Spark Join Strategies

    • Mar

      26

      Explore how to tune Spark Joins using hints and how they work behind the scenes

      Wed 3/2611:00 PM—12:30 AM (UTC)
    2 more items • Free preview

Week 3

Mar 31—Apr 6

    Apr

    2

    A special Q&A session featuring a Senior Data Engineer from Netflix

    Wed 4/211:00 PM—12:00 AM (UTC)

    Self Study Week

    0 items

Week 4

Apr 7—Apr 13

    Hello UDF, Goodbye Performance – A Costly Love Story ❤️💀

    • Apr

      9

      How to optimize a Spark job with UDF? Vectorize

      Wed 4/911:00 PM—12:30 AM (UTC)
    1 more item

Week 5

Apr 14—Apr 20

    My Life is Skewed: The Mean Lies, and p99 is a Chaos Goblin! 😂🔥

    • Apr

      16

      How to handle Skew in Spark Jobs

      Wed 4/1611:00 PM—12:30 AM (UTC)

Week 6

Apr 21—Apr 27

    Low Latency, High Stakes: Cracking Spark Interviews at FAANGM

    • Apr

      23

      Walk Through Commonly Asked Questions in FAANGM interviews

      Wed 4/2311:00 PM—12:30 AM (UTC)

Week 7

Apr 28—May 4

    The Art of Table Organization: Partitioned, Clustered & Everything In Between

    • Apr

      30

      Unpartitioned Tables, Partitioned Tables, Over-Partitioned Tables, Zorder and Liquid Clustering

      Wed 4/3011:00 PM—12:30 AM (UTC)
    2 more items • Free preview

Week 8

May 5—May 8

    How to crack your next interview? How to create job opportunities?

    • May

      7

      Ask Me Anything + Q&A

      Wed 5/711:00 PM—12:00 AM (UTC)

What people are saying

        Jitesh was incredible! His sole goal is to help you improve and he goes above and beyond to achieve that. In addition to his depth and breadth of knowledge, his commitment to the student sets him apart from other coaches. I highly recommend a session with Jitesh.
Jarriett K Robinson

Jarriett K Robinson

Senior Data Engineer, Netflix
        Jitesh had been very helpful to guide me throughout the interview. He is very quick to respond and goes above and beyond to help. It would not have been possible for me to crack the interview without his guidance. I would highly recommend him
Minu Sarraf

Minu Sarraf

Data Engineer, Amazon
        Your posts on the whitepapers as well as the associated videos do an excellent job of providing a high-level summary while still providing enough technical information to be useful on the job. For example, I had always heard that Spark processed data lazily, but I never understood the benefits of that lazy processing until watching your lecture. Th
Billy Switzer

Billy Switzer

Data Engineer & Architect, PrudentRx
        Excellent, constructive suggestions. Very professional. Stayed beyond our time limit to ensure we could reason through every step. Highly recommended!
Benjamin Tew

Benjamin Tew

Solution Architect, Snowflake
        Jitesh has been amazing to work with and provided a lot of insight to the interview process, and has given me tools to succeed in this interview and future ones.
Sunny Nian

Sunny Nian

Software Engineer, Autodesk

Meet your instructor

Jitesh Soni

Jitesh Soni

Jitesh Soni is a highly experienced Data Architect and Engineer with over 13 years in the industry, having worked at AWS, Databricks, and Amazon. He holds a Master’s in Big Data from Simon Fraser University and has a proven track record of solving real-world data challenges. In 2024 alone, he worked on 150 use cases across 110 customers, helping businesses take workloads to production almost every week. As a mentor and educator, he has helped countless professionals upskill and land better-paying roles by breaking down complex concepts with a no-fluff, practical approach. His insights, shared under the pen name Canadian Data Guy, have been viewed over a million times across Substack, Medium, YouTube, and LinkedIn.


Why learn from Jitesh?

Hands-on experience: 13+ years in data engineering, including AWS, Databricks & Amazon

Proven impact: Helped 110+ companies take workloads to production in 2024 alone

Trusted mentor: Professionally mentoring for 3+ years, guiding people to high-paying roles

No fluff, practical learning: Focuses on real-world applications, not just marketing hype

Recognized thought leader: 1M+ views across platforms, sharing deep technical insights

A pattern of wavy dots

Join an upcoming cohort

Spark Deep Dive: Cost-Effective Strategies to Scale to Petabytes

Cohort 1

$500

Dates

Mar 18—May 8, 2025

Payment Deadline

Mar 20, 2025
Get reimbursed

There is a more than 90% chance that you will finish a cohort based course --Study by Harvard & MIT

There is a more than 90% chance that you will finish a cohort based course --Study by Harvard & MIT

Active hands-on learning

This course builds on live workshops and hands-on projects

Interactive and project-based

You’ll be interacting with other learners through breakout rooms and project teams

Learn with a cohort of peers

Join a community of like-minded people who want to learn and grow alongside you

Frequently Asked Questions

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A pattern of wavy dots

Join an upcoming cohort

Spark Deep Dive: Cost-Effective Strategies to Scale to Petabytes

Cohort 1

$500

Dates

Mar 18—May 8, 2025

Payment Deadline

Mar 20, 2025
Get reimbursed

$500

8 Weeks