Data Architect (Databricks, BigQuery)

Overview

Lead the design and implementation of enterprise-scale data warehouse platforms on Databricks and Snowflake, establishing data modeling standards, governance frameworks, and scalable ingestion pipelines. Collaborate with cross-functional teams and engage with clients as a trusted advisor to drive data strategy and architecture blueprints.

What You'll Do11

• 1Lead enterprise-scale implementation of data warehouse data platforms on Databricks and Snowflake environments.
• 2Design and implement Medallion (Bronze/Silver/Gold) architecture and scalable enterprise data models.
• 3Establish data modeling standards (dimensional, data vault, lakehouse patterns) and ensure best practices across projects.
• 4Establish enterprise data governance frameworks including cataloging, lineage, stewardship, and compliance using Atlan.
• 5Define and implement CI/CD pipelines for infrastructure and data platform deployments.
• 6Design data architectures that support AI/ML and Generative AI workloads including vector storage, feature layers, and secure access patterns.
• 7Build scalable ingestion frameworks supporting batch, streaming, and CDC pipelines.
• 8Architect secure, high-performance data integration layers for analytics, BI, and AI consumption.
• 9Develop target-state architecture blueprints and enforce data standards, governance, and best practices across teams.
• 10Collaborate with engineering, analytics, and data science teams to ensure platform alignment and scalability.
• 11Engage with clients as a trusted advisor, driving data strategy, roadmap definition, and identifying opportunities for expansion.

Requirements9

• 1Minimum 8+ years of experience in Data Architecture / Data Engineering, with exposure in enterprise-scale data platform modernization initiatives.
• 2Minimum 3+ years of deep hands-on experience in Databricks-based lakehouse architecture on AWS, including large-scale data platform implementations.
• 3Strong expertise in Databricks ecosystem including Delta Lake, Databricks SQL, Unity Catalog, Delta Live Tables, and MLflow with focus on performance optimization and security.
• 4Strong experience with AWS data services including S3, Glue, EMR, Lambda, Redshift, Athena, Lake Formation, and DMS, with strong understanding of cloud-native architecture patterns.
• 5Proven experience designing and implementing Medallion (Bronze/Silver/Gold) architecture, scalable data models (Dimensional/Data Vault), and enterprise lakehouse platforms supporting batch and real-time processing.
• 6Hands-on experience building scalable ingestion frameworks including batch, streaming, and CDC pipelines using tools like Kafka, Kinesis, Spark, or similar technologies.
• 7Proven experience implementing CI/CD pipelines for data platforms, including infrastructure as code, automated deployments, and environment management.
• 8Hands-on experience enabling data platforms for AI/ML and Generative AI use cases, including feature stores, vector storage, and secure data access patterns.
• 9Experience with orchestration tools such as Apache Airflow or MWAA and designing integration layers for analytics, BI, and AI consumption.

Who Should Apply

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