Primary Skills
- Snowflake data architecture and data engineering
- ETL Fundamentals, Zero Copy Cloning, SQL, SQL (Basic + Advanced), Python, Data Warehousing, Snowflake Data Exchange, Time Travel and Fail Safe, Snowpipe, SnowSQL, Modern Data Platform Fundamentals, Data Modelling Fundamentals, PLSQL, T-SQL, Stored Procedures
Job requirements
- Location: San Francisco, CA (5 days onsite)
- Experience Range: 12 - 15 years of experience, including significant hands-on expertise in Snowflake data architecture and data engineering
- Key Responsibilities:
- Design and implement scalable Snowflake data architectures to support enterprise data warehousing and analytics needs
- Optimize Snowflake performance through advanced tuning, warehousing strategies, and efficient data sharing solutions
- Develop robust data pipelines using Python and DBT, including modeling, testing, macros, and snapshot management
- Implement and enforce security best practices such as RBAC, data masking, and row-level security across cloud data platforms
- Architect and manage AWS-based data solutions leveraging S3, Redshift, Lambda, Glue, EC2, and IAM for secure and reliable data operations
- Orchestrate and monitor complex data workflows using Apache Airflow, including DAG design, operator configuration, and scheduling
- Utilize version control systems such as Git to manage codebase and facilitate collaborative data engineering workflows
- Integrate and process high-volume data using Apache ecosystem tools such as Spark, Kafka, and Hive, with an understanding of Hadoop environments
- Required Skills:
- Advanced hands-on experience with Snowflake, including performance tuning and warehousing strategies
- Expertise in Snowflake security features such as RBAC, data masking, and row-level security
- Proficiency in advanced Python programming for data engineering tasks
- In-depth knowledge of DBT for data modeling, testing, macros, and snapshot management
- Strong experience with AWS services including S3, Redshift, Lambda, Glue, EC2, and IAM
- Extensive experience designing and managing Apache Airflow DAGs and scheduling workflows
- Proficiency in version control using Git for collaborative development
- Hands-on experience with Apache Spark, Kafka, and Hive
- Solid understanding of Hadoop ecosystem
- Expertise in SQL (basic and advanced), including SnowSQL, PLSQL, and T-SQL
- Strong requirement understanding, presentation, and documentation skills; ability to translate business needs into clear, structured functional/technical documents and present them effectively to stakeholders.
- Preferred Skills:
- Experience with Salesforce Data Cloud integration
- Familiarity with data cataloging tools such as Alation
- Exposure to real-time streaming architectures
- Experience working in multi-cloud environments
- Knowledge of DevOps or DataOps practices
- Certifications in data cloud technologies
- Desired Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field
- Relevant certifications in Snowflake, AWS, or data engineering technologies are highly desirable
