Data Architect

Job Title:

Data Architect - Enterprise Analytics Transformation (Snowflake / Databricks)

Experience:

10+ Years Role Summary

We are seeking a highly experienced Data Architect to lead the design and implementation of modern enterprise data platforms supporting large-scale Analytics Transformation, Data Modernization, AI/ML, and Cloud Migration initiatives. The ideal candidate will have deep expertise in Snowflake and/or Databricks, modern data architecture patterns, and cloud-native solutions.

This role will be responsible for defining enterprise data strategy, architecting scalable data platforms, enabling self-service analytics, and driving transformational programs that deliver business value through data.

• Define and own enterprise data architecture strategy aligned with business and analytics objectives.
• Design scalable, secure, and high-performance data platforms using Snowflake and/or Databricks.
• Architect enterprise-wide Data Warehouses, Data Lake houses, Data Lakes, and Analytics Platforms.
• Lead architecture decisions across structured, semi-structured, and streaming data environments.
• Establish architecture standards, frameworks, governance models, and best practices.

• Lead data modernization initiatives involving migration from legacy platforms such as Teradata, Oracle, Netezza, SQL Server, Hadoop, and Informatica.
• Design target-state architectures for enterprise analytics and reporting.
• Enable self-service BI and advanced analytics platforms.
• Drive Data Mesh, Data Fabric, and Lakehouse adoption strategies.
• Support AI/ML and GenAI enablement through scalable data architecture.

• Design and optimize Snowflake architecture including:
• Virtual Warehouses
• Data Sharing
• Snowpark
• Data Marketplace
• Security & Governance
• Performance Optimization

OR

• Design and optimize Databricks Lakehouse architecture including:
• Unity Catalog
• Medallion Architecture
• Spark Optimization
• Data Governance
• Real-Time Processing
• Define scalable ETL/ELT frameworks and ingestion patterns.
• Architect batch, real-time, and streaming data solutions.
• Establish data quality, lineage, metadata management, and governance processes.
• Design integration patterns across enterprise applications and external data sources.

• Collaborate with business stakeholders, product owners, analytics teams, and executive leadership.
• Present architecture roadmaps, recommendations, and business cases to leadership teams.
• Lead architecture review boards and governance forums.

• Mentor Data Engineers, Analytics Engineers, and Solution Architects.
• Define technology standards, reusable frameworks, and reference architectures.
• Drive innovation and adoption of emerging cloud and data technologies.

• 10+ years of experience in Data Engineering, Data Warehousing, Data Architecture, or Analytics.
• 5+ years of experience designing cloud data platforms.
• Proven experience leading Enterprise Analytics Transformation or Data Modernization programs.
• Experience designing solutions supporting large-scale enterprise reporting, analytics, and AI initiatives.

• Snowflake Data Cloud
• Databricks Lakehouse Platform
• AWS Data Services
• Data Warehousing
• Data Lakehouse Architecture
• Data Lakes
• ETL/ELT Frameworks
• SQL Optimization
• Python
• Real-Time Data Processing

• Data Quality Frameworks
• Metadata Management
• Master Data Management (MDM)
• Data Catalogs
• Data Security & Compliance
• AWS

• Snowflake Migration Programs
• Databricks Lakehouse Implementations
• Tableau, Power BI, Looker
• Enterprise Data Strategy & Roadmap Development
• Global Delivery Models

• Snow Pro Advanced Architect

• Databricks Certified Data Architect

• Microsoft Azure Solutions Architect Expert
• AWS Solutions Architect Professional
• Google Professional Cloud Architect
• TOGAF Certification
• Certified Data Management Professional (CDMP)

An ideal candidate will have successfully architected and delivered multiple Enterprise Analytics Transformation Programs, leading modernization initiatives from legacy environments to Snowflake and/or Databricks Lakehouse architectures. The individual should possess deep expertise in enterprise data strategy, cloud platforms, analytics architecture, governance, and stakeholder management, enabling organizations to accelerate data-driven decision-making and AI adoption at scale.