The Analytics Engineering team at Gusto operates as a comprehensive unit, overseeing data, analytics, and operational excellence to ensure the availability, reliability, and utility of trusted data. As an Analytics Engineer within the Data team, your primary responsibility will be to define and take ownership of datasets crucial for our data practitioners. These datasets play a key role in developing metrics, conducting analyses, and ensuring that Gusto makes well-informed decisions based on high-quality data.

Gusto is currently seeking an experienced Senior Analytics Engineer to join our team, contributing to the development and maintenance of foundational data infrastructure essential for the expansion and scalability of our initiatives across various business domains. In this position, you will create and maintain data products widely utilized to empower individuals throughout the organization in exploring and addressing data-related inquiries. This entails managing significant portions of our data from end to end, with a focus on transformation, design, documentation and user-friendliness.

Reporting to the Head of Analytics Engineering, this role involves close collaboration with Data Analysts, Data Science, Engineering, and other cross-functional teams as needed.

Here’s what you’ll do day-to-day:

• Design and implement Gusto's production data warehouse, defining a set of schemas to enhance data analysis for various business use cases. Develop use-case-specific data tables by skillfully combining and engineering essential elements across diverse data domains.
• Construct robust data ingestion pipelines from both internal and external sources, including APIs, ensuring structural integrity, adherence to data quality standards, and establishing traceability from the consumption layer back to the raw data layer.
• Empower users throughout the organization to independently explore and answer data-related queries using well-organized and intuitive datasets.
• Lead Quality Assurance and Data Quality initiatives to streamline development timelines, minimize errors, and uphold the reliability of analytical products. Implement monitoring mechanisms for crucial tables.
• Optimize data warehousing processes by refining naming conventions, enhancing data modeling, and implementing best practices for data quality testing.
• Offer recommendations to enhance the reliability, user-friendliness, and performance of the Data Team's technical infrastructure.
• Working with other Analytics Engineers to share thoughts, offer recommendations, provide mentorship to ensure the team is operating with the best practices.

Here’s what we’re looking for:

• 7+ years of experience handling extensive and intricate datasets sourced from diverse channels, including product, marketing, sales, finance, operations, and customer acquisition.
• Significant work experience in Data Modeling and Data Architecture within a production environment, specifically with distributed databases like Redshift.
• Expertise designing, building and deploying production data pipelines/ETLs in Python (Airflow and dbt experience a plus)
• Extensive understanding of relational databases and familiarity with the modern data stack.
• Ensure data integrity and accuracy by conducting regular data audits, identifying and resolving data quality issues, and implementing data governance best practices.
• Stellar SQL skills, with specific experience in Redshift as a notable advantage.
• Experience in BI and data visualization (Tableau experience a plus).

Our cash compensation amount for this role is targeted at $140,000-$174,000/year in Denver, Chicago, Miami, Austin and Atlanta, $153,000-$189,000/year in Los Angeles and Seattle, and $170,000- $210,000/year for San Francisco and New York.