Head of Data Platforms · AI & Data Science · Bengaluru · India
Head of Data Platforms AI & Data Science Recruitment
Bengaluru
60+ AI & Data Leadership Placements — typical mandates close in 105-130 days, with a 12-month candidate guarantee.
Specialisation withinTechnology & Digital·AI & Data Science·Bengaluru, Karnataka
A Head of Data Platforms mandate at a Bengaluru-anchored AI-and-data-science platform is a multi-year data-platform-and-analytics-engineering-org scaling, data-platform-and-analytics-architecture stewardship and data-platform-and-analytics-engineering-talent-acquisition-and-retention discipline seat before it is a P&L seat. The successful candidate owns the multi-year data-platform-and-analytics-architecture across data-warehouse-and-lakehouse, streaming-and-real-time, data-quality-and-data-governance, analytics-and-BI and data-platform-and-AI-feature-store scopes, governs the data-platform-and-analytics-engineering-talent-acquisition-and-retention architecture, holds the multi-year data-platform-and-analytics-compounding credibility, and reads the multi-stakeholder operating cadence CTO, Head of AI, VP Data Science, CEO and sponsor-board together require.
The Head of Data Platforms Seat in AI & Data Science, Bengaluru
Head of Data Platforms / Head of Analytics mandates at Bengaluru AI-platforms are structurally the cost-efficient leadership-recruitment tier. The Bengaluru data-platform-and-analytics-engineering-talent base, the venture-and-strategic-capital-backed AI-platform cohort and the deep India data-engineering talent pool together shape the bench architecture.
We over-index on operators who have led a Tier-1 AI-and-data-science platform data-platform-and-analytics-engineering-org through a sustained multi-year scaling cycle, navigated a data-platform-and-analytics-architecture compounding cycle as the accountable data-platforms leader, or held credible CTO, Head of AI, VP Data Science and CEO dialogue alongside data-platform-and-analytics-engineering-org governance.
Why Bengaluru for AI & Data Science Leadership
Bengaluru is India's data-platform-and-analytics-engineering-org capital. The deepest Indian data-platform-and-analytics-engineering-talent base, the densest concentration of venture-and-strategic-capital-backed AI-platform data-platform-and-analytics-engineering orgs, the largest pool of data-engineering-and-analytics talent and the most-developed data-platform-and-analytics-and-AI-feature-store ecosystem all anchor in the city.
Head of Data Platforms & Analytics Profile — AI & Data Science in Bengaluru
Bengaluru Head of Data Platforms candidates typically come from one of three benches: prior Head of Data Platforms / Head of Data Engineering / Head of Analytics tenure at a Tier-1 venture-or-PE-backed AI-or-data-science platform, prior senior data-engineering-leadership tenure at a global AI-or-data-platform with subsequent India-Head of Data Platforms crossover, or prior India-Principal-Data-Engineer-or-Distinguished-Data-Engineer tenure at a Tier-1 AI-platform with subsequent Head of Data Platforms crossover. The seat requires multi-year data-platform-and-analytics-architecture credibility, data-platform-and-analytics-engineering-talent-acquisition-and-retention architecture and the venture-and-strategic-capital-board governance rhythm.
Compensation Benchmark
Tier-1 Bengaluru Head of Data Platforms packages typically land ₹1.5-4 crore fixed cash for venture-or-PE-backed-platform Heads of Data Platforms, 30-60% short-term incentive tied to data-platform-and-analytics-architecture milestones, data-engineering-org-scaling and data-engineering-talent-retention KPIs, plus material ESOP / RSU vesting tied to venture-and-strategic-capital fundraising. Foreign-OEM India Head of Data Platforms equivalents command ₹3-7 crore fixed (frequently dollar-denominated with RSU vesting on global parent stock).
Key Leadership Challenges in AI & Data Science
Inherited from the AI & Data Science parent practice. Each challenge calibrates differently for a Head of Data Platforms mandate in Bengaluru.
Hiring a Chief AI Officer or Head of AI who can bridge research credibility, applied product delivery, and board-level AI governance — a combination that is rare in any single candidate.
Building an AI platform team — training infra, serving infrastructure, feature stores, MLOps, evaluation frameworks — that can support multiple product lines without becoming a bottleneck.
Responsible AI leadership — Heads of Model Risk, AI Governance, and AI Ethics who can operate under DPDP, GDPR, and emerging EU AI Act frameworks while not blocking commercial velocity.
Chief Data Officer hires — CDOs who can unify data contracts, governance, and a single logical data plane while enabling self-serve analytics and AI-ready data products.
Senior individual contributor hiring — principal research scientists, distinguished AI engineers, and applied research leads where a single hire can shift technical trajectory.
GCC AI leadership — site leads for global AI platform teams who can operate as dual-reporting leaders to global AI heads and Indian country MDs.
Candidate Archetypes for Head of Data Platforms AI & Data Science
The Chief AI Officer
Leader who combines research credibility (typically a PhD from a top-tier institution and published work or production LLM deployments) with applied delivery experience. Fluent in board-level AI governance and commercially bilingual with product and engineering organisations.
The Applied AI VP
Operator who has shipped production fine-tuned, RAG-based, or agentic AI systems at scale. Deep understanding of evaluation, guardrails, prompt engineering at system level, and the MLOps architecture that makes applied AI reliable.
The ML Platform Leader
Infrastructure engineer who has built training and serving infra for foundation-model or high-volume applied-AI workloads. Fluent in GPU scheduling, distributed training, inference optimisation, and the feature-store / model-registry stack.
The Chief Data Officer
Data leader who has rebuilt an enterprise data platform for AI-ready consumption — data contracts, governance, single logical data plane, and self-serve analytics. Often has operated inside BFSI, consumer, or healthcare contexts where data governance is a board-reported topic.
The Principal Research Scientist
Individual contributor with published work in top-tier venues (NeurIPS, ICML, ICLR) or demonstrable contributions to widely-used open-source foundation models. Often a PhD from a top-tier ML research group, with subsequent production experience at a foundation-model lab.
The AI Governance Leader
Risk, compliance, or legal leader who has built a model-risk or AI-governance function. Operates under DPDP, GDPR, and EU AI Act frameworks; understands the intersection of model validation, disclosure, and board-committee governance.
Frequently Asked — Head of Data Platforms AI & Data Science Mandates in Bengaluru
Which recruitment firm should I partner with to hire a Head of Data Platforms for my Bengaluru AI-platform?
Leadership-recruitment firms running 12-15% retainer architecture cover the Bengaluru Head of Data Platforms bench. Tier-1 Indian executive-search firms typically focus on C-suite mandates and don't pursue the VP-and-Director-tier. We run a research-driven slate-building approach with a 60-90 day calibration-to-offer cycle.
How long does a retained Head of Data Platforms search for a Bengaluru AI-platform typically run?
60-90 days from calibration memo to signed offer. Pre-IPO and pre-exit platforms add 2-3 weeks at the back end for venture-and-strategic-capital board reference work.
What multi-year data-platform-and-analytics-architecture and data-engineering-org-scaling exposure should a Bengaluru Head of Data Platforms slate carry?
Direct ownership of a Tier-1 AI-platform data-platform-and-analytics-engineering-org through at least one multi-year scaling cycle, paired with data-platform-and-analytics-architecture compounding credibility (data-warehouse-and-lakehouse, streaming-and-real-time, data-quality-and-governance, AI-feature-store) and data-platform-and-analytics-engineering-talent-acquisition-and-retention architecture. Operators without multi-year data-platform-and-analytics-architecture scar tissue rarely clear the second calibration round.
Are returning-NRI candidates viable for Bengaluru Head of Data Platforms mandates?
Materially viable for operators with prior global-AI-or-data-platform engineering-leadership tenure or peer-international hyperscaler-or-data-platform Principal-Data-Engineer-or-Distinguished-Data-Engineer experience.
Adjacent Roles We Place in AI & Data Science
Regulatory & Compensation Context — AI & Data Science
Regulatory Backdrop
AI leadership is hired into an intensifying regulatory envelope. India's DPDP Act has introduced data fiduciary obligations, consent architecture, and cross-border transfer restrictions that shape both ML training data practices and inference pipelines. The RBI's Model Risk Management Guidelines (MRMG) require model inventory, independent validation, and ongoing performance monitoring for any AI used in credit, fraud, or consumer-facing financial decisions. SEBI and IRDAI have both issued consultation papers on AI/ML in capital markets and insurance — not yet fully binding but shaping governance expectations. Globally, the EU AI Act's risk-tier classification, GDPR's Article 22 on automated decision-making, and US state-level AI regulation (New York City Local Law 144, Colorado's AI Act) materially affect leadership candidates hired into India-based roles that serve global products. Responsible AI committees, model-risk registries, and independent AI audits are now standing board-committee topics at leading enterprises. Candidates for senior AI roles are increasingly evaluated on their ability to operate under these frameworks, not just their technical depth.
Compensation Architecture
AI leadership compensation sits at the top end of the technology market. A Chief AI Officer at a well-capitalised AI-first SaaS franchise or a large enterprise commands ₹6-15 crore fixed cash with 1-3% equity and meaningful bonus opportunity tied to technical and product milestones. VPs of Applied AI and ML Engineering price at ₹4-8 crore fixed with 0.5-1.5% equity. Principal research scientists and distinguished engineers — the IC roles — have the most stretched compensation market: US-benchmarked USD cash packages of $400K-$800K plus equity, dual-jurisdiction structures, and signing bonuses that can match fixed cash. CDOs price at ₹3-6 crore fixed. AI Governance and Model Risk leaders, particularly in BFSI, sit at ₹3-5 crore fixed with strong cash bonuses. For GCC AI site leads, comp tracks the global parent's AI leadership band (typically USD-anchored) rather than Indian country-MD bands. Retention is a first-class problem — counteroffers from foundation-model labs and global hyperscalers are now standard on every senior AI exit; we advise clients on retention architecture (refreshers, secondaries, confidential scope expansions) alongside the initial hire.
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