Data Engineering for Banks & Fintech — Prashant Dave (Bajaj Finserv) | Dawdle Podcast

In this episode of the Dawdle podcast, Rishikesh interviews Prashant Dave, Vice President — Data Engineering at Bajaj Finserv, about building and operating large-scale data platforms in BFSI. Prashant brings 20 years of hands-on experience across banking, e-commerce and logistics to explain how enterprises move from Excel-era reporting to petabyte-scale data engineering, while ensuring governance, compliance and security.

Key topics covered:

How the role and scale of data changed over the last decade (Excel → petabytes).

Challenges in standardizing, structuring and discovering multi-format data (structured, images, audio, video).

Modern BI tools, democratization of insights, and access governance.

Data privacy, DPDP (data protection) trends, and implications for enterprises.

Encryption, zero-trust, logging, audit trails and practical InfoSec controls.

Hybrid cloud & data residency strategies (cost vs compliance trade-offs).

AI/ML impact on BFSI: fraud detection, monitoring, signal vs noise, and reliability limits.

Data engineering priorities for large BFSI: discoverability, governance, access control (including column-level), and automation.

🎙️ Guest: Prashant Dave — Vice President, Data Engineering, IT, Bajaj Finserv
📌 Perfect for: Data leaders, CIOs, CTOs, data engineers, compliance officers, founders building data platforms & HR of tech orgs.

⏱ Chapters / Timestamps

00:00 – Welcome & guest introduction
00:27 – Prashant’s 20-year data journey (MIS → data engineering → data science)
01:15 – How the role of data evolved: Excel to petabytes
02:49 – Challenges of scaling data platforms: multi-format data & standardization
04:39 – The danger of quick decisions before standardizing data
05:20 – Data sources diversity and its operational impact
06:00 – Modern BI tools: democratization and governance features
07:33 – Access management & data protection concerns
08:32 – Misuse of platforms and lead-generation vs. primary use cases
10:00 – Ransomware, cyber threats & the role of risk/compliance teams
11:33 – DPDP/DPDPA & auditing as enforcement mechanisms
12:55 – New startup opportunities: data governance monitoring
13:28 – VAPT and vulnerability assessments — accuracy limits
13:57 – Encryption, hashing & protecting PII at scale
15:30 – Preventing misuse: corporate email policies & InfoSec monitoring
17:21 – Continuous compliance: audits, data discoverability dashboards, access hygiene
20:36 – Data residency, hybrid approaches & cloud cost trade-offs
22:10 – Region selection and compliance implications for BFSI
23:09 – Audit trails, logging and accountability in data ops
24:07 – AI/ML impact in BFSI: fraud detection & operational analytics — realities vs expectations
27:27 – Accuracy limits of AI and the need for cross-checks
28:22 – Future of data engineering: discoverability, governance, column-level access controls
30:11 – Closing thoughts & thanks

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