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 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

Principal Data Engineer - R01560587

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