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
Open Positions
1
Skills Required
Databricks, Presales, Architecture
Location
Chennai, Tamil Nadu, India
Role
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
Up-to-date 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
Education/Qualification
UG/PG
Desirable Skills
presales
Job Title
Databricks Solution Architect – Pre Sales
Years Of Exp
12 to 18 years
Job Code
10380
Designation
Databricks Solution Architect – Pre Sales
Posted On
:
01-Jun-2026
📌 Databricks Solution Architect – Pre Sales (India)
🏢 Goavega
📍 India