Principal Data Engineer - R01560587

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

• 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