Project Role : Data Platform Architect
Project Role Description : Architects the data platform blueprint and implements the design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models.
Must have skills : Databricks Unified Data Analytics Platform
Good to have skills : NA
Minimum
15 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
This is a senior delivery and solution leadership role responsible for shaping data platform solutions, leading large scale Lakehouse implementations, owning RFP responses, and managing multi pod delivery teams.
This role balances hands on architectural guidance with execution ownership, client leadership, and people development.
Key Responsibilities
Lead end to end delivery of enterprise scale Lakehouse and Data Platform programs across multiple teams and workstreams.
Own solution architecture and technical approach for complex client engagements, in alignment with Data Mesh, Data Products, and Lakehouse paradigms.
Drive RFP responses, estimations, solution write ups, and client presentations for Data & AI opportunities.
Provide strong technical leadership across PySpark, Delta Lake, DLT, Unity Catalog, and cloud native data engineering stacks.
Oversee design and build of scalable ingestion, transformation, and analytics pipelines using Databricks best practices.
Guide governance implementation using Unity Catalog, including access controls, lineage, classification, and compliance guardrails.
Ensure performance optimization, cost efficiency, security, and reliability across platforms and workloads.
Act as the primary escalation point for delivery risks, architectural decisions, and cross team dependencies.
Collaborate closely with client stakeholders, product owners, and platform teams to align outcomes with business objectives.
Mentor solution architects, leads, and senior engineers build strong technical depth and leadership pipeline.
Contribute to capability development, accelerators, reference architectures, and reusable assets.
Stay current with Databricks innovations including Mosaic AI, Lakehouse Federation, Vector Search, and Model Serving, and guide adoption pragmatically.
Required Skills & Experience
20+ years of experience in Data Engineering, Analytics, or Data Platform roles.
Strong experience leading large scale Databricks Lakehouse implementations.
Hands on experience with PySpark, Delta Lake, DLT, Asset Bundles, and Databricks SQL.
Solid understanding of cloud platforms (Azure / AWS / GCP) and cloud native data services.
Strong background in data modeling, data warehousing, and analytical design patterns.
Proven experience in stakeholder management, delivery governance, and program leadership.
Excellent communication skills for executive, client, and internal leadership interactions.
Good to Have
Databricks Professional certifications or equivalent.
Experience with dbt, Airflow, and CI/CD for data platforms.
Exposure to GenAI, ML pipelines, or AI enabled analytics solutions.
Experience supporting industry specific data platforms (Insurance, BFSI, Health, Retail, etc.).
Qualification:
- 15 years full time education is required.
