Staff Analytics Engineer

7+ years of progressive experience in analytics engineering, data engineering, or a similar role. Familiarity with data producers supporting Financial, Marketing, and Sales data initiatives. Mastery of developing modular and reusable data models (e.g. star schemas, snowflake schemas). Expert-level proficiency with cloud data warehousing technologies such as Snowflake (preferred), Redshift, or BigQuery. Extensive experience developing and optimizing complex ETL/ELT programs and data pipelines using tools like DBT, Fivetran, Airflow. Proficient in building polished dashboards in tools like Looker, Sigma, Tableau. Expertise in prompt engineering and design for LLMs (e.g., GPT). Demonstrated ownership of full life cycle data analytics development. Exceptional presentation, communication, and interpersonal skills. Intermediate to Advanced Python proficiency. Intermediate to Advanced experience with a wide range of Machine Learning and analytical techniques. Strong strategic thinking, problem-solving, and decision-making capabilities. A bachelor’s or master’s degree in Computer Science, Technology, Engineering, or a related field; or equivalent deep industry experience.

Architect, design, and lead the implementation of highly complex, scalable, and resilient data solutions in the cloud. Build subject matter expertise in specific business areas and data domains. Support defining and executing the overarching strategy for the analytics engineering function. Lead efforts in designing, building, and maintaining a robust, governed, and scalable semantic layer. Spearhead the technical vision and roadmap for data quality and governance. Act as a primary technical consultant to senior executives and business stakeholders. Mentor, coach, and develop junior and mid-level analytics engineers. Set standards for documentation, conduct advanced peer code reviews, and define comprehensive testing strategies. Continuously evaluate and champion new technologies and methodologies.