Interview with Sinchan Banerjee

Sinchan Banerjee is the author of Scalable Data Architecture with Java, we got the chance to sit down and find out more about his experience of writing with Packt.

Q: What are your specialist tech areas?

Sinchan: I am a Principal Data architect with vast experience in designing, architecting and delivering data engineering solutions for big data and real time data ingestion and analytics use-cases, across different on-premises and cloud platforms.

Q: How did you become an author for Packt? Tell us about your journey. What was your motivation for writing this book?

Sinchan: Having a keen interest in data-related technologies and my love for sharing my knowledge right from the beginning of my career, I published multiple papers, wrote few blogs, created many course contents, and provided training in Big Data and Java. However, I never thought of publishing a book, until Packt publication approached me in June 2021 to write a book for Java Data architects and aspiring Data architects. I found this to be an interesting opportunity to share my knowledge from years of experience in building and delivering Data Engineering solutions.

Q: What kind of research did you do, and how long did you spend researching before beginning the book?

Sinchan: My insight on why this book is needed comes from my years of interactions with data engineers, data analysts, business SMEs and architects. Although there are materials, which discuss data architecture in general or specific data technologies in depth, I couldn’t find a material, which discusses and practically explains how a data architect should approach a problem and recommend solutions by using logical inferences. This is a kind of book I would recommend learners who wants to know how to build solid, well-thought scalable data architectures, using modern tech stack and cloud.

Q: Did you face any challenges during the writing process? How did you overcome them?

Sinchan: Yes, I primarily faced two challenges while writing this book. Firstly, considering the vastness of the topic and years of experience in that field, it was challenging to decide what needs to be incorporated in the book and what needs to be filtered out, so, that the contents are concise and easy to understand, yet they are extensive and complete in terms of knowledge. Secondly, the technologies related to data engineering is very dynamic. So, the contents had to be revisited from time to time to ensure that the book is keeping up with the technological changes. This meant that some retesting of the finished code or rewriting few sections was necessary.

Q: What’s your take on the technologies discussed in the book? Where do you see these technologies heading in the future?

Sinchan: There are a lot of technologies and platform used in this book. Most of them are very popular today like Apache Spark, Apache Kafka, AWS Services and so on. While few of them are gaining popularity with growing community like DaaS(Data-as-a-Service), GraphQL, Apache NIFI and DataOps. I believe that these technologies will be the backbone of creating data engineering solutions for the near future.

Q: Why should readers choose this book over others already on the market? How would you differentiate your book from its competition?

Sinchan: There are many books and online materials that discuss data architectures in general. There are other sets of books and online materials that focus on a single technology and dives deep into the technology stack. While such materials provide architects with essential knowledge, they often lack details on how an architect should approach a data engineering problem practically and create the best-suited architecture by using logical inference. In this book, I have tried to formalize a few techniques by which a data architect can approach a problem to create effective solutions.

Q: What are the key takeaways you want readers to come away with from the book?

Sinchan: By the end of this book, reader will be able to:
1. Clearly decide when to choose what data format, data storage, database, data model and data platform.
2. Clearly decide the most optimal architectural pattern and solution to be applied for a given data engineering problem.
3. Choose correct technology stack based for the chosen architecture.
4. Implement the chosen solution, along with Data governance and Performance Engineering.
4. Evaluate and Recommend the best architectural alternative based on data driven metrics and chart.

Q. What advice would you give to readers learning tech? Do you have any top tips?

Sinchan: Data technologies are very dynamic, so, you should always set aside time to learn newer tools and technologies to keep up with the changes. Developing a broad skillset is necessary for today’s data engineering, however, you should develop few areas of expertise.

Q. Do you have a blog that readers can follow?

Sinchan: You can follow me on LinkedIn or on my blog:

Q. Can you share any blogs, websites and forums to help readers gain a holistic view of the tech they are learning?

Sinchan: There are a vast amount of varied topics covered in the book. Wherever required, I have provided blog/online material references in the book itself.

Q. How would you describe your author’s journey with Packt? Would you recommend Packt to aspiring authors?

Sinchan: As a first time author, I liked how Packt has refined and streamlined the process of writing a book, so that the journey of the author becomes smooth and hassle free. Also, Packt provided a wonderful team of people consisting of editors, project managers, tech reviewers and marketers , who helped me in each phase of writing and releasing the book.

Q. Do you belong to any tech community groups?

Sinchan: Yes, I do. I am part of the EDM Council and multiple local tech community groups like AWS Cincinnati, Cincinnati Apache Kafka meetup by Confluent etc.

Q. What are your favorite tech journals? How do you keep yourself up to date on tech?

Sinchan: I follow springeropen journals for big data and data analytics. Apart from that, I attain multiple seminars, webinars, conferences and read online blogs/materials to keep myself up-to-date.

Q. How did you organize, plan, and prioritize your work and write the book?

Sinchan: It might sound very simple but the key for me was early to bed and early to rise. This helped me spent solid one to two hours on book writing every day before my office began. I spent these hours in designing the content and developing and testing the example use-cases. However, a bulk of book writing and incorporating editorial comments was done over the weekend.

Q. What is that one writing tip that you found most crucial and would like to share with aspiring authors?

Sinchan: Patience and Consistency. Keep in mind writing a book is a long process and months of commitment, along with balancing your day job.

Q. Would you like to share your social handles? If so, please share.

Sinchan: LinkedIn:

You can find Sinchan’s book on Amazon by following this link: Please click here

Scalable Data Architecture with Java is Available on


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