Principal Data Engineer – R01560587

Principal Data Engineer - R01560587 Principal Data Engineer 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 workflowsIntegrate 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-SQLStrong 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 practicesCertifications 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 Salary: 140-150 USD per year salary