Data Platform Architect

Overview

Delivery and solution leadership role balancing hands-on architectural guidance with execution ownership, client leadership, and people development. The role architects the data platform blueprint and implements the design, including relevant data platform components, and collaborates with Integration Architects and Data Architects to ensure cohesive integration between systems and data models.

What you'll do

• Architect the data platform blueprint and implement the design, encompassing the relevant data platform components.
• Collaborate with Integration Architects and Data Architects to ensure cohesive integration between systems and data models.
• Lead implementation of Unity Catalog: create catalogs, schemas, role-based access policies, lineage visibility, and data classification tagging (PII, PHI, etc.).
• Guide organization-wide governance via Unity Catalog setup: workspace linkage, SSO, audit logging, external locations, and Volume access.
• Enable cross-platform data access using Lakehouse Federation, querying live from externally hosted databases.
• Leverage and integrate Databricks Marketplace to consume high-quality third-party data and publish internal data assets securely.
• Govern and manage Delta Sharing for securely sharing datasets with external partners or across tenants.
• Design and maintain PII anonymization, tokenization, and masking strategies using DBX functions and Unity Catalog policies to meet GDPR/HIPAA compliance.
• Architect Power BI, Tableau, and Looker integration with Databricks for live reporting and visualization over governed datasets.
• Build Databricks SQL Dashboards to enable stakeholders with real-time insights, KPI tracking, and alerts.
• Design and build complex pipelines using Delta Lake, Auto Loader, Delta Live Tables (DLT), and deployment using Asset Bundles.
• Architect data ingestion and transformation using DLT Expectations, modular Databricks Functions, and reusable pipeline components.
• Apply performance optimization techniques.
• Lead cross-functional initiatives across data science, analytics, and platform teams to deliver secure, scalable, and value-aligned data products.
• Provide thought leadership on adopting advanced features like Mosaic AI, Vector Search, Model Serving, and Databricks Marketplace publishing.

What you'll need

• Proven experience as a Data Architect and Data Engineer leading enterprise-scale Lakehouse initiatives.
• Expert-level understanding of modern Data & Analytics Architecture patterns including Data Mesh, Data Products, and Lakehouse Architecture.
• Excellent programming and debugging skills in Python.
• Strong experience with PySpark for building scalable and modular ETL/ELT pipelines.
• Must have hands-on expertise in at least one major cloud platform: AWS, GCP, or Azure.
• Experience with cloud-based services relevant to data engineering, data storage, data processing, data warehousing, real-time streaming, and serverless computing.
• Strong background in data modeling and data warehousing concepts.
• Must have skill: Databricks Unified Data Analytics Platform.
• Minimum 12 years of experience is required.
• Educational qualification: 15 years full time education is required.

Nice to have

• Working knowledge of DBT (Data Build Tool).
• Certifications: Databricks Certified Professional or similar certifications.
• Knowledge of machine learning concepts and experience with popular ML libraries.
• Knowledge of big data processing (e.g., Spark, Hadoop, Hive, Kafka).
• Data orchestration experience with Apache Airflow.
• Knowledge of CI/CD pipelines and DevOps practices in a cloud environment.
• Experience with ETL tools like Informatica, Talend, Matillion, or Fivetran.
• Familiarity with DBT (Data Build Tool).

Details

• Location: Bengaluru.