Lead Data Engineer
Primary Skills
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
Specialization
Snowflake Data Architecture: Lead Data Engineer
Job requirements
Key Responsibilities: • Collaborate with Product Management to understand and evaluate use cases, as well as functional and technical requirements. • Conduct data discovery and analysis of source systems to identify the necessary data to fulfill business requirements. • Develop conceptual and logical data models to validate requirements, pinpointing essential entities and relationships with full documentation of assumptions/risks. • Translate logical data models into physical data models for Salesforce Data Cloud, including the production of source-to-target mapping documentation that outlines data movement from source to destination and specifies transformation rules. • Support engineering teams through the implementation of physical data models, including source-to-target mapping and the application of transformation/business rules. Minimum Qualifications: • 10+ years of hands-on experience in data modeling and design for OLTP and analytical systems. • Solid understanding of data modeling principles and best practices, with expertise in canonical and semantic data modeling concepts. • Proficiency in at least one data modeling software (e.g., ER Studio, ERwin). • 10+ years of experience in data analysis and profiling using SQL and other relevant tools. Preferred Qualifications: • Experience with our technology stack, including Salesforce Data Cloud, Marketing Cloud, and Tableau, is highly desirable. • Practical experience with sales and marketing data. • Experience working with globally distributed teams is an advantage. • Availability to work in the Pacific time zone.
