Analytics Engineer

FiscalNote is a leader in policy and global intelligence that combines data, technology, and insights to help organizations turn critical information into action. The Analytics Engineer will build scalable dbt data models, reporting capabilities, and analytics solutions that support operational efficiency, customer experience, financial performance, and enterprise decision-making.

Responsibilities:

• Build and maintain dbt models with SQL and Jinja for analytics and dataops across departments including finance, product, sales, and customer success
• Harden analytics models via tests, freshness checks, constraints, etc. to ensure the quality and correctness of our data
• Create reports and dashboards in Metabase using the visual query builder
• Conduct ad-hoc analysis to understand our data in depth and answer business questions
• Collaborate with stakeholders across the organization to understand their respective business domains and design analytics solutions for them

Requirements:

• You are curious, thoughtful, and detail-oriented
• You see technical challenges as puzzles to solve, and can generalize a solution to an individual problem out to an entire class of problems
• You dislike doing the same thing manually over and over and enjoy automating systems
• You take pride in your work and do not like leaving things half-done
• You can operate independently, but have support from your team as needed
• You are proficient in SQL and have hands-on experience building data models in dbt
• You know how to explore and analyze unfamiliar datasets and find insights in the data
• You want to deepen your technical expertise and may have experience with Python or other general-purpose programming languages
• 4+ years in analytics engineering, data analysis, or a related technical role
• Excellent data modeling proficiency with an eye toward simplicity and modularity
• Advanced proficiency in SQL, including complex joins, window functions, and CTEs
• Production experience in at least one dbt project
• Strong dimensional, relational, or semantic data modeling skills
• Familiarity with structured, semi-structured and unstructured data formats
• Experience with data visualization products such as Metabase, Looker, and Tableau
• Ability to explore and analyze complex datasets
• Strong communication skills and ability to write thorough, high-quality documentation
• Basic statistical analysis to identify trends, outliers, etc
• Git-based development, pull requests, code review, and CI/CD
• Experience with Snowflake and SnowSQL (preferred)
• Experience with Metabase (preferred)
• Python proficiency (preferred)
• Experience performing data munging and analysis with tools and environments like Pandas/Polars and Jupyter Notebooks (preferred)