- 12–18 years of overall experience in data, analytics, big data, and cloud platforms
- 7–10+ years in solution architecture roles spanning data engineering, analytics, and platform modernization
- 5+ years in a customer‑facing pre‑sales / solutioning role, supporting RFPs, proposals, and POCs for large enterprise clients
Pre‑Sales & Solution Architecture Experience
- Proven experience leading pre‑sales technical engagements, including discovery workshops, requirement analysis, architecture definition, and executive‑level presentations
- End‑to‑end ownership of solution shaping for data platform programs, covering:
- Current‑state assessment and gap analysis
- Target architecture and migration roadmap
- Effort estimation, sizing models, assumptions, risks, and dependencies
- Hands‑on ownership of POCs / pilot engagements, including scope definition, success criteria, demo execution, and outcome articulation
- Strong experience supporting RFP/RFQ responses, creating architecture diagrams, solution narratives, delivery approaches, and commercial inputs in collaboration with sales and delivery teams
Databricks & Modern Data Platform Experience
- Hands‑on experience architecting solutions on Databricks Lakehouse / Data Intelligence Platform, including:
- Batch and streaming ingestion patterns
- Medallion (Bronze / Silver / Gold) architecture
- Delta Lake‑based storage and processing
- Unity Catalog‑driven governance and security
- Strong experience designing cloud‑native data platforms on Azure, AWS, or GCP, including storage, compute, networking, security, and cost considerations
- Experience integrating Databricks with the broader ecosystem such as BI tools, orchestration frameworks, CI/CD pipelines, and enterprise monitoring platforms
Leadership & Stakeholder Engagement
- Experience engaging with CxO, data leaders, and enterprise architects, translating business goals into scalable technical solutions
- Ability to articulate technology trade‑offs and architectural decisions to both technical and non‑technical stakeholders
- Experience mentoring junior architects/engineers and contributing reusable assets such as reference architectures, accelerators, and demo frameworks
Preferred / Domain Exposure
- Exposure to AI/ML and MLOps concepts and AI‑ready data platform architectures
- Experience driving large‑scale legacy modernization (EDW Lakehouse, Hadoop/Spark Databricks, BI modernization)
- Domain experience in BFSI, Insurance, Retail, Healthcare, or Telecom is a strong advantage
- 12–18 years of overall experience in data, analytics, big data, and cloud platforms
- 7–10+ years in solution architecture roles spanning data engineering, analytics, and platform modernization
- 5+ years in a customer‑facing pre‑sales / solutioning role, supporting RFPs, proposals, and POCs for large enterprise clients
Pre‑Sales & Solution Architecture Experience
- Proven experience leading pre‑sales technical engagements, including discovery workshops, requirement analysis, architecture definition, and executive‑level presentations
- End‑to‑end ownership of solution shaping for data platform programs, covering:
- Current‑state assessment and gap analysis
- Target architecture and migration roadmap
- Effort estimation, sizing models, assumptions, risks, and dependencies
- Hands‑on ownership of POCs / pilot engagements, including scope definition, success criteria, demo execution, and outcome articulation
- Strong experience supporting RFP/RFQ responses, creating architecture diagrams, solution narratives, delivery approaches, and commercial inputs in collaboration with sales and delivery teams
Databricks & Modern Data Platform Experience
- Hands‑on experience architecting solutions on Databricks Lakehouse / Data Intelligence Platform, including:
- Batch and streaming ingestion patterns
- Medallion (Bronze / Silver / Gold) architecture
- Delta Lake‑based storage and processing
- Unity Catalog‑driven governance and security
- Strong experience designing cloud‑native data platforms on Azure, AWS, or GCP, including storage, compute, networking, security, and cost considerations
- Experience integrating Databricks with the broader ecosystem such as BI tools, orchestration frameworks, CI/CD pipelines, and enterprise monitoring platforms
Leadership & Stakeholder Engagement
- Experience engaging with CxO, data leaders, and enterprise architects, translating business goals into scalable technical solutions
- Ability to articulate technology trade‑offs and architectural decisions to both technical and non‑technical stakeholders
- Experience mentoring junior architects/engineers and contributing reusable assets such as reference architectures, accelerators, and demo frameworks
Preferred / Domain Exposure
- Exposure to AI/ML and MLOps concepts and AI‑ready data platform architectures
- Experience driving large‑scale legacy modernization (EDW Lakehouse, Hadoop/Spark Databricks, BI modernization)
- Domain experience in BFSI, Insurance, Retail, Healthcare, or Telecom is a strong advantage
