About the role

Databricks Solution Architect – Pre Sales

Job Description

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

Roles & Responsibilities

Pre‑Sales & Deal Shaping

Lead customer discovery sessions to understand business objectives, current data landscapes, constraints, and success metrics
Define target‑state architectures, solution options, and phased transformation roadmaps
Drive technical evaluations and solution positioning in partnership with Account Executives
Design and lead demonstrations, workshops, and POCs to validate architecture and value propositions
Develop proposal‑quality deliverables including architecture diagrams, estimates, delivery approach, risks, assumptions, and dependencies
Present solutions to senior technical and executive stakeholders with clear business value articulation

Databricks & Architecture Responsibilities

Design end‑to‑end Lakehouse architectures for batch, near‑real‑time, and streaming workloads
Define governance, security, and data access strategies using Unity Catalog
Architect scalable ingestion, transformation, and orchestration patterns
Recommend performance optimization and cost‑management strategies
Define CI/CD, environment promotion, and automation patterns for data platforms

Key Skills

Databricks & Lakehouse Platform

Databricks Lakehouse / Data Intelligence Platform architecture
Apache Spark (batch & streaming), Spark SQL, performance tuning
Delta Lake (ACID transactions, schema evolution, time travel)
Databricks Workflows / Jobs, cluster policies, workspace design
Unity Catalog – data governance, access control, lineage, auditability

Modern Data Platform & Cloud

Cloud‑native data architectures on Azure / AWS / GCP
Data ingestion & integration patterns (batch, near‑real‑time, streaming)
Data warehousing & analytics concepts (EDW modernization, ELT patterns)
Integration with BI/Analytics tools (Power BI, Tableau, Looker)
Data platform security, compliance, and non‑functional requirements

Pre‑Sales & Solutioning

Technical discovery and use‑case framing
Architecture definition, solution alternatives, and trade‑off analysis
POC design and execution (scope, success metrics, demos)
Proposal development – architecture diagrams, sizing, estimates, risks & assumptions
Stakeholder communication from engineering teams to CxO audiences

Engineering & Enablement

Programming/scripting: Python, SQL (working knowledge of Scala preferred)
CI/CD concepts, repo‑based development, DevOps for data platforms
Cost optimization, scalability, and reliability patterns
Ability to create reusable reference architectures, accelerators, and demo assets

Certifications (Preferred / Good to Have)

Databricks

Databricks Certified Solutions Architect
Databricks Certified Data Engineer (Associate / Professional)
Databricks Certified Machine Learning Professional (nice to have)

Cloud Platforms

Azure : Azure Solutions Architect Expert, Azure Data Engineer Associate
AWS : AWS Solutions Architect (Associate / Professional), Data Analytics – Specialty
GCP : Professional Data Engineer or Cloud Architect

Complementary (Optional)

TOGAF or enterprise architecture frameworks
FinOps / cloud cost management certifications
Security & data governance certifications

Mandatory Skills

Databricks, Architect,presales

Budget - open ended from client side, please share best possible budget from your side

Contract duration - 3 to 6months+