A senior Data Architect is sought to lead the design, development, and governance of sophisticated data architectures. This role focuses on modern cloud data platforms, particularly Snowflake and Databricks, to support advanced analytics, AI/ML, and enterprise-wide data initiatives. The ideal candidate is a strategic thinker capable of transforming business needs into robust, scalable technical solutions.

This position emphasizes ensuring data quality, security, and scalability throughout the architecture lifecycle. You will play a pivotal role in shaping the future of our data landscape by creating high-performance, reliable data systems that drive business value and innovation.

Design and implement comprehensive data architectures within Snowflake and Databricks environments. Establish clear data modeling standards, encompassing dimensional, normalized, and Data Vault approaches. Architect resilient data lakes, lakehouses, and data warehouses, adhering to industry best practices. Lead data integration initiatives utilizing ETL/ELT frameworks and tools such as ADF, dbt, and Spark. Optimize the performance and cost-efficiency of Snowflake and Databricks operations.

Implement robust data governance, security, lineage, and compliance frameworks. Develop architectures for both real-time and batch data processing. Collaborate closely with business stakeholders to ensure data strategy aligns with organizational objectives. Mentor engineering teams and uphold architectural standards across the organization.

A minimum of 16 years of experience is required for this Sr. Lead Data Architect position. Proven expertise in designing and implementing large-scale data platforms, with extensive experience in both Snowflake and Databricks within enterprise settings. Strong proficiency in SQL, Python, and distributed data processing frameworks. Hands-on experience with major cloud platforms like Azure, AWS, or GCP and their associated services.

Solid understanding of data ingestion, transformation, orchestration, and data warehousing concepts is crucial. Experience with data visualization tools such as Power BI, Tableau, or Qlik is beneficial. Experience enabling AI/ML data pipelines is highly preferred, and relevant certifications in Snowflake, Databricks, or cloud platforms are a significant advantage. Excellent stakeholder management, communication, and leadership skills are essential.