Overview
About the Position
Full job description
About the Position 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. #LI-AL1
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
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)
Tips for this job
Practical Job and Scholarship guidance. These tips do not replace official rules or create new eligibility requirements.
- Tailor the CV and application to the responsibilities and required skills stated on the official employer page.
- Use concrete evidence of relevant work, projects and measurable results rather than generic claims.
- Confirm location, work authorization, remote restrictions and sponsorship terms before applying.
- Apply through the original employer or official recruitment destination shown on this page.
Verification notes
laptop-ats-crawler v2
Job and Scholarship is the discovery and verification layer. Confirm eligibility, dates, salary/funding and application instructions on the original source before submitting anything.
fiscalnote (lever) ↗Browse current Job and Scholarship listings from fiscalnote (lever) →