We are seeking a seasoned Principal Data Architect with a proven track record in architecting and managing large-scale data platforms, specifically leveraging Snowflake. This role demands deep expertise in complex database migrations, cost optimization, and identifying strategic business service opportunities through data insights. You will be a key leader in driving our data-centric initiatives, ensuring scalability, efficiency, and alignment with our business objectives.
Strategic Data Architecture & Migration Leadership:
- Develop and execute comprehensive data strategies, with a primary focus on Snowflake, to support enterprise-wide data initiatives.
- Lead complex, large-scale database migrations to and from Snowflake, ensuring minimal disruption and data integrity.
- Design and implement robust data migration strategies, including data validation, performance tuning, and cutover planning.
- Experience with data lake architectures (e.g., AWS S3, Azure Data Lake Storage, Google Cloud Storage).
- Proficiency in data visualization and reporting tools such as Power BI and Tableau.
- Experience with other analytics and big data technologies (e.g., Spark, Hadoop, Kafka).
- Experience with Data Lakehouse architecture implementation.
- Experience with real time data processing.
Snowflake Platform Mastery & Optimization:
- Architect and optimize Snowflake data models, data pipelines, and data warehousing solutions for high performance and scalability.
- Implement advanced Snowflake features and best practices to maximize platform efficiency and minimize operational costs.
- Proactively monitor and optimize Snowflake performance through query tuning, data clustering, and resource management.
Cost Optimization & Business Value Creation:
- Develop and implement strategies to optimize Snowflake costs, including resource utilization, storage management, and query optimization.
- Identify and leverage data insights to drive business service opportunities, improve operational efficiency, and generate revenue.
- Translate business requirements into actionable data architecture solutions that deliver measurable business value.
Data Governance & Security:
- Establish and enforce data governance policies and standards, ensuring data quality, consistency, and compliance with regulatory requirements.
- Implement robust data security measures within Snowflake and across the data ecosystem, protecting sensitive data from unauthorized access.
- Design and implement data lineage and metadata management strategies.
Cloud Data Platform Leadership:
- Design and implement scalable and resilient cloud-based data architectures, leveraging Snowflake's cloud-native capabilities.
- Integrate Snowflake with other cloud services and data platforms to create a cohesive and efficient data ecosystem.
- Implement infrastructure as code (IaC) to streamline deployment and management of data infrastructure.
Collaboration & Mentorship:
- Collaborate with business stakeholders, data engineers, data scientists, and other teams to understand data requirements and deliver effective solutions.
- Provide technical leadership and mentorship to data engineers and other data professionals, fostering a culture of continuous learning and innovation.
- Communicate complex technical concepts to non-technical stakeholders.
Qualifications:
- 10+ years of progressive experience in data architecture, data warehousing, and database migration.
- Expert-level knowledge of Snowflake architecture, features, and best practices.
- Proven experience in leading large-scale database migrations to and from Snowflake.
- Demonstrated ability to optimize Snowflake performance and costs.
- Strong understanding of data modeling, data integration, and ETL/ELT processes.
- Experience with cloud platforms (AWS, Azure, GCP) and cloud data warehousing solutions.
- Expertise in SQL and data modeling tools.
- Strong understanding of data governance, security, and compliance.
- Excellent problem-solving, analytical, and communication skills.
- Proven ability to lead and mentor technical teams.
- Experience with performance monitoring tools.
Preferred Qualifications:
- Snowflake certifications (e.g., SnowPro Core, SnowPro Advanced).
- Experience with data visualization and reporting tools.
- Experience with best practices for data pipelines.
- Experience with Python or other scripting languages.
- Experience with data cataloging tools.
- Experience with data mesh architecture.
Nice to have:
- Experience with data science and machine learning workflows.
- Experience with Snowflake's AI/ML capabilities (e.g., Snowpark ML, external functions for AI integration).
- Experience integrating AI/ML models with Snowflake for predictive analytics, anomaly detection, or other data-driven insights.
- Familiarity with leveraging AI for automated data governance, data quality improvement, or cost optimization within Snowflake.
- Experience with implementing generative AI use cases with snowflake data.