Snowflake Data Architect

Job Summary

We are seeking an experienced Snowflake Data Architect to design, develop, and implement scalable, secure, and high-performance enterprise data architecture solutions using Snowflake. The ideal candidate will have strong expertise in cloud data warehousing, data modeling, ETL/ELT architecture, data integration, and data governance. This role will involve defining data architecture standards, leading data modernization initiatives, and collaborating with business and technical teams to deliver enterprise data solutions.

Key Responsibilities

• Design and implement scalable, high-performance data warehouse architectures using Snowflake.
• Define enterprise data architecture strategies, standards, frameworks, and best practices for cloud-based data platforms.
• Develop and maintain conceptual, logical, and physical data models, including dimensional modeling, star schema, snowflake schema, and data vault modeling.
• Architect and optimize ETL/ELT pipelines for integrating data from multiple source systems into Snowflake.
• Design and implement Snowflake features such as Virtual Warehouses, Databases, Schemas, Stages, Streams, Tasks, Snowpipe, Dynamic Tables, and Snowpark.
• Lead data migration and modernization initiatives from traditional data warehouses and platforms such as Oracle, SQL Server, Teradata, and Hadoop to Snowflake.
• Establish data ingestion, transformation, orchestration, and integration strategies using tools such as Informatica, Talend, dbt, Matillion, Fivetran, or similar platforms.
• Implement data security, governance, access control, and compliance frameworks using RBAC, masking policies, row access policies, and data classification.
• Optimize Snowflake performance through query tuning, warehouse sizing, clustering, caching, workload management, and cost optimization.
• Define and implement data quality, data validation, metadata management, lineage, and master data management practices.
• Integrate Snowflake with cloud platforms such as AWS, Azure, and GCP, including cloud storage and data processing services.
• Establish CI/CD and DevOps practices for database development, deployment, version control, and automated testing.
• Provide technical leadership and architectural guidance to data engineers, developers, and ETL teams.
• Collaborate with business stakeholders, enterprise architects, data engineers, and analytics teams to translate business requirements into technical architecture.
• Create architecture diagrams, technical design documents, data flow diagrams, and solution specifications.

Required Skills & Qualifications

• 10+ years of experience in data engineering, data warehousing, database architecture, or related roles.
• 4+ years of hands-on experience with Snowflake architecture and cloud data warehousing.
• Strong expertise in Snowflake architecture, including Virtual Warehouses, Micro-partitions, Clustering, Time Travel, Zero-Copy Cloning, and Secure Data Sharing.
• Extensive experience in SQL, advanced SQL, stored procedures, and query optimization.
• Strong understanding of data modeling concepts, including dimensional modeling, star schema, snowflake schema, and data vault.
• Experience designing enterprise-scale ETL/ELT pipelines and complex data integration solutions.
• Hands-on experience with one or more ETL/ELT tools such as Informatica, Talend, Matillion, Fivetran, dbt, or DataStage.
• Strong knowledge of at least one cloud platform: AWS, Azure, or GCP.
• Experience with Python, PySpark, or Snowpark for data processing and automation.
• Knowledge of data governance, data security, metadata management, data lineage, and data quality frameworks.
• Experience with performance tuning, workload optimization, and Snowflake cost management.
• Familiarity with orchestration tools such as Apache Airflow, Azure Data Factory, AWS Glue, or similar.
• Experience with CI/CD tools such as Jenkins, Git, Azure DevOps, or GitHub Actions.

Preferred Qualifications

• Snowflake SnowPro Core or SnowPro Advanced certifications.
• Experience with enterprise data lakehouse and modern data platform architecture.
• Knowledge of Kafka, Spark, Hadoop, and real-time/streaming data integration.
• Experience with BI and analytics tools such as Power BI, Tableau, or Looker.
• Familiarity with data governance platforms such as Collibra, Alation, or Informatica Axon.
• Experience working in Agile/Scrum environments and leading distributed engineering teams.

Key Technical Skills

Snowflake: Snowflake Architecture, SnowSQL, Snowpipe, Streams, Tasks, Dynamic Tables, Snowpark, Time Travel, Zero-Copy Cloning, Secure Data Sharing.

Data Architecture: Enterprise Data Architecture, Data Warehousing, Data Modeling, Dimensional Modeling, Data Vault, Data Lakehouse.

ETL/ELT: Informatica, Talend, dbt, Matillion, Fivetran, DataStage.

Cloud Platforms: AWS, Azure, GCP, S3, Azure Data Lake, Google Cloud Storage.

Programming: SQL, Advanced SQL, Python, PySpark.

Data Governance: Data Quality, Data Lineage, Metadata Management, Data Security, RBAC, Data Masking.

DevOps & Orchestration: Jenkins, Git, Azure DevOps, Airflow, AWS Glue, Azure Data Factory.