Seeking a seasoned Data Architect with extensive experience in Snowflake and Databricks. This pivotal role involves crafting and overseeing high-performance, scalable data architectures tailored for advanced analytics, AI/ML initiatives, and broader enterprise data strategies. The ideal candidate possesses a strategic vision to translate complex business needs into robust technical solutions, prioritizing data integrity, security, and scalability.

This position demands a forward-thinking professional capable of bridging business objectives with cutting-edge data technologies, ensuring seamless data flow and actionable insights.

Design and implement comprehensive data architectures utilizing Snowflake and Databricks. Establish and enforce data modeling standards, including dimensional, normalized, and Data Vault approaches. Architect scalable data lakes, lakehouses, and data warehouses incorporating industry best practices. Lead data integration efforts through ETL/ELT frameworks, leveraging tools like ADF, dbt, and Spark. Optimize performance and manage costs across Snowflake and Databricks environments. Develop and deploy robust data governance, security, lineage, and compliance frameworks. Enable architectures supporting both real-time and batch data processing. Collaborate closely with business stakeholders to align data strategy with organizational goals. Mentor engineering teams and uphold architectural standards.

Extensive expertise in Snowflake, covering architecture design, Snowpipe, Streams/Tasks, performance tuning, and data sharing. Advanced proficiency in Databricks, including Delta Lake, Lakehouse architecture, Spark (PySpark/Scala), and performance optimization. Hands-on experience with Databricks features like Unity Catalog, Delta Live Tables, MLflow, and Mosaic AI. Strong command of SQL, Python, and distributed data processing frameworks. Practical experience with cloud platforms (Azure/AWS/GCP) and their associated services. Solid understanding of data ingestion, transformation, orchestration, and data warehousing principles. Familiarity with data visualization tools such as Power BI, Tableau, or Qlik. Proven ability to design hybrid architectures, optimizing Snowflake for warehousing and Databricks for analytics/ML. Experience in defining data lakehouse strategies for diverse data types. Capability to build event-driven, real-time data pipelines. Proficiency in establishing reusable frameworks for data processes. Experience in implementing comprehensive data governance, cataloging, lineage, and quality controls. Knowledge of enterprise security policies and regulatory compliance. Skill in defining access control strategies using role-based and attribute-based methods. Minimum 10 years of overall experience in data engineering and architecture. Demonstrated experience with both Snowflake and Databricks in enterprise settings. Strong background in designing large-scale data platforms and migration strategies. Experience in enabling AI/ML data pipelines is highly valued. Excellent stakeholder management and communication skills. Ability to translate technical concepts into business value. Leadership capabilities with team management experience. Strong problem-solving and analytical acumen.