Analytics Engineer

About the Role

At FiscalNote, we build platforms that connect people to their governments, and our Data Analytics team builds tools, processes, and reporting capabilities to integrate operational data and enable enterprise decision making. As an Analytics Engineer on the Data Analytics team, you recognize the value of properly managing, analyzing and reporting data to improve operational efficiencies, customer experience, and financial performance, and want to build the data models and analytics capabilities that empower decision making across the company. You will work closely with our product and operations teams to build clean, scalable analytics models which are the backbone of our reporting and advanced analytics capabilities. This role reports to the Director of Data Analytics & Business Intelligence.

About The Team

The Data Analytics team sits at the intersection of data, technology, and strategy at FiscalNote. We build and maintain the systems, models, and reporting infrastructure that enable the entire business to operate with clarity and confidence. Our work connects every function from sales to finance to customer success, ensuring that the right data reaches the right people at the right time to drive informed decisions. Our core mission is to understand the business and impact decision-making across all departments through the effective use of data. We are AI-forward but we do not vibe code. Experience with AI and agentic harnesses is a plus but not required for this role.

About You

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.

Applicants must be currently authorized to work in the United States on a full-time basis. We are unable to sponsor or take over sponsorship of an employment visa at this time.

What to Expect

• 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

What Sets You Apart

• 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)