Presales Lead

Presales Lead - Data Platform Modernization (Cloud / On-Prem)

Company: Smart Analytica Location: Pune, India Experience: 10+ years Type: Full-time

About Us

Smart Analytica is a Data and AI company with 100+ PB of data engineered in production, 250+ engineers, and partnerships across Microsoft, AWS, Google Cloud, Databricks, and Snowflake. Our Migration Suite accelerators (ProbeX, KodeX, ReconX, SynthX) power modernization pursuits across India, the US, and the Middle East.

The Role

Own presales for our Data Platform Modernization portfolio - Modern Data Platform, Cloud Modernization, and Cloudera Big Data services. You'll shape deals from discovery to proposal defense, converting legacy estates (Teradata, Netezza, CDH/HDP, Informatica, etc.) into winnable modernization roadmaps on Cloudera CDP, Databricks, and hyperscaler-native stacks.

Responsibilities

• Lead end-to-end presales: discovery, solution architecture, estimation, RFP/RFI responses, and proposal defense.
• Design target-state lakehouse architectures and apply the 6 R's framework to map workloads to modernization patterns.
• Scope and price engagements - readiness audits, migration pilots, and cohorts - with TCO/ROI business cases.
• Demo our accelerators and co-sell with Cloudera, Databricks, and hyperscaler partner teams.
• Build reusable presales assets (reference architectures, estimation models, case studies) and mentor solution engineers.

Must-Haves

• 10+ years in data platform delivery/architecture, with 5+ years in presales or solution consulting for data/cloud services.
• Track record of winning large modernization or migration deals ($1M+ TCV / PB-scale).
• Deep expertise in at least two of: Cloudera/Hadoop ecosystem (CDH/HDP CDP), legacy DWs (Teradata, Netezza, Oracle), or cloud Lakehouse targets (Databricks, Fabric, BigQuery, Snowflake).
• Strong estimation, proposal writing, and CxO-level storytelling skills; willingness to travel.

Good-to-Haves

Cloudera / Databricks / hyperscaler certifications; experience in regulated industries (BFSI, capital markets, telecom); FinOps exposure; familiarity with AI-readiness themes (semantic layers, RAG on governed data).

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