Seeking a seasoned Data Architect with extensive experience in modern cloud data platforms like Snowflake and Databricks. This pivotal role involves architecting, developing, and overseeing scalable data solutions essential for advanced analytics, AI/ML, and broader enterprise data initiatives. A strategic mindset is crucial for translating business needs into robust technical designs, ensuring data integrity, security, and scalability.

This position demands a visionary leader capable of crafting high-performance data architectures that drive innovation and support critical business objectives.

Design and implement comprehensive data architectures within Snowflake and Databricks environments. Define and enforce data modeling standards, including dimensional, normalized, and Data Vault approaches. Architect resilient data lakes, lakehouses, and data warehouses, adhering to best practices. Lead data integration efforts using ETL/ELT frameworks with tools like ADF, dbt, and Spark. Optimize performance and manage costs across Snowflake and Databricks deployments. Establish and manage data governance, security, lineage, and compliance frameworks. Develop architectures for both real-time and batch data processing. Collaborate with stakeholders to align data strategies with business goals. Mentor engineering teams and uphold architectural integrity.

Possess strong expertise in Snowflake, covering architecture, Snowpipe, Streams/Tasks, performance tuning, and data sharing. Demonstrate advanced knowledge of Databricks, including Delta Lake, Lakehouse architecture, Spark (PySpark/Scala), and performance optimization. Familiarity with Databricks features such as Unity Catalog, Delta Live Tables, MLflow, and Mosaic AI is beneficial. Proficiency in SQL, Python, and distributed data processing frameworks is essential. Experience with cloud platforms like Azure, AWS, or GCP and their associated services is required. Solid understanding of data ingestion, transformation, orchestration, and data warehousing principles. Experience with data visualization tools like Power BI, Tableau, or Qlik is advantageous. Proven ability to design hybrid architectures, integrating Snowflake for warehousing and Databricks for analytics and ML. Skills in defining data lakehouse strategies for diverse data types are needed. Experience building event-driven, real-time data pipelines is expected. Capability to establish reusable frameworks for data ingestion, transformation, and consumption is key. Implement robust data governance, cataloging, lineage, and quality controls. Ensure adherence to enterprise security policies and regulatory compliance. Define effective access control strategies using role-based and attribute-based approaches. Minimum of 10 years of overall experience in data engineering and architecture. Demonstrated experience with both Snowflake and Databricks in enterprise settings. Strong track record in designing large-scale data platforms and migration strategies. Experience in enabling AI/ML data pipelines is highly desirable. Relevant certifications are a plus.