Data Platform Architect

Job Description: Senior Data Platform Architect

Experience: 1218+ Years
Location: Bangalore / Chennai
Role Type: Senior Architecture / Technical Leadership

Job Summary

We are looking for a highly experienced Senior Data Platform Architect with deep expertise in Databricks architecture and enterprise-scale data platform design. The ideal candidate will have strong architectural ownership and the ability to envision, design, and enhance modern data platforms covering data ingestion, transformation, data quality, profiling, and governance.

The candidate will be responsible for evaluating open-source and commercial technologies, developing reusable architecture frameworks, enriching the existing Reference Architecture (RA), and translating architectural concepts into actionable development requirements. The role requires close collaboration with customers, product vendors, and implementation partners to drive platform innovation and accelerate delivery.

Experience with Apache NiFi, Cloudera, and on-premises data platforms will be a significant advantage.

Key Responsibilities

• Enterprise Data Platform Architecture: Design and define end-to-end data platform architectures, with a strong focus on Databricks, Lakehouse architecture, Delta Lake, Unity Catalog, and enterprise data engineering.
• Data Platform Capabilities: Architect reusable frameworks for data ingestion, transformation, data quality, data profiling, and data governance.
• Architecture-to-Delivery Translation: Break down architectural capabilities into Epics, Features, User Stories, and Tasks to enable effective implementation by engineering teams.
• Technology Evaluation: Assess open-source and commercial technologies to identify solutions that accelerate platform development, including Apache NiFi-based data ingestion frameworks.
• Internal Tools and Frameworks: Understand and leverage existing assets, including the Data Engineering Toolkit, Data Ingestion Framework, and Neoware CodeX, to improve reusability and development efficiency.
• Reference Architecture: Understand the existing enterprise Reference Architecture, identify improvement opportunities, and contribute to its evolution and standardization.
• Cloudera and On-Premises Platforms: Develop an understanding of Cloudera-based on-premises data platforms and their integration with modern data platform architectures.
• Vendor and Stakeholder Engagement: Lead technical discussions with Databricks, Cloudera, other product vendors, customers, and implementation partners.
• Technical Leadership: Provide architectural guidance to engineering teams, validate design decisions, and ensure alignment with enterprise standards and strategic technology roadmaps.

Mandatory Skills and Experience

• 12–18+ years of overall IT experience, with substantial experience in data platform architecture and design.
• Deep, hands-on architectural expertise in Databricks-based enterprise implementations.
• Strong understanding of Lakehouse architecture, Delta Lake, Unity Catalog, and enterprise data engineering architecture.
• Proven experience designing end-to-end data platforms, including ingestion, transformation, data quality, and profiling.
• Experience defining reusable data frameworks, architecture patterns, and platform capabilities.
• Ability to evaluate technologies and translate architectural requirements into Epics, Features, User Stories, and Tasks.
• Experience contributing to enterprise Reference Architectures, technical roadmaps, and architecture standards.
• Strong technical communication skills, with the ability to engage customers, vendors, and cross-functional engineering teams.

Good-to-Have Skills

• Experience with Apache NiFi and reusable data ingestion frameworks.
• Exposure to Cloudera, Hadoop ecosystem technologies, and on-premises data platforms.
• Experience evaluating open-source and commercial data platform technologies.
• Familiarity with the Data Engineering Toolkit, Data Ingestion Framework, or Neoware CodeX.
• Databricks certification.
• TOGAF certification or equivalent enterprise architecture experience.

Ideal Candidate Profile

The ideal candidate is a true Data Platform Architect, not just a data engineer or Databricks developer. They should be able to conceptualize the capabilities required for a modern enterprise data platform, make architecture-level technology decisions, define reusable frameworks, and guide engineering teams from architecture through implementation.

Candidates must be able to explain real-world Databricks architecture implementations, including platform design decisions, governance, scalability, integration patterns, and architectural trade-offs.

Candidates Who Are Not a Fit

• Data Engineers whose experience is limited to Python, SQL, PySpark, and pipeline development.
• Databricks developers who have not owned platform-level architecture and design.
• Project Managers who primarily coordinate delivery without strong technical architecture expertise.
• Solution Architects focused exclusively on applications, Java, or infrastructure without substantial data platform experience.
• Candidates who mention Databricks on their resumes but cannot explain the architecture and design decisions of a real implementation.