Senior Analytics Engineer, Analytics Enablement

About the role

You will own the design and delivery of self-serve analytics solutions that remove bottlenecks and accelerate data adoption across Fullscript. You will diagnose where teams get stuck and translate those needs into repeatable tooling, assets, and workflows that scale. A core part of your work will be enabling others through clear training, documentation, and hands-on support so they can answer questions with confidence. You will use SQL, Python, and BI platforms such as Looker to build AI-powered analytics tools that are both powerful and practical. You will partner closely with Analytics, Data Science, and Data Engineering to align on definitions, patterns, and infrastructure standards. Your role will require you to own projects end-to-end, navigating ambiguous problems and designing practical approaches where the path is not obvious. You will strengthen the systems around data access and usage so teams can find the right data and use the right tools. Ultimately, you will build the foundations that help more people across Fullscript self-serve trustworthy data without relying on analysts or data scientists for every question.

Key facts

What you'll do

Partner with stakeholders across Fullscript to uncover recurring data needs, self-serve gaps, and patterns that can be addressed through shared tooling and reusable assets.

Design and implement self-serve analytics solutions such as trusted datasets, reporting foundations, templates, and workflows that make data easier to access and use independently.

Surface and consume data more effectively through BI tools and internal tooling, prioritizing usability, consistency, trust, and adoption across teams.

Build scalable solutions using SQL, Python, and BI platforms such as Looker, including AI-powered analytics tools developed internally to meet evolving needs.

Create and deliver training, documentation, office hours, and hands-on enablement sessions that teach teams how to use tools, find data, and analyze it effectively on their own.

Partner with Analytics, Data Science, and Data Engineering teams to strengthen the infrastructure, patterns, and definitions that support self-serve analytics across the business.

Own projects end-to-end, navigating ambiguous problems where the right approach is not immediately clear and designing practical paths from discovery to implementation.

Improve the overall experience of data by making it more accessible, reliable, and understandable for practitioners who rely on it to deliver care.

Champion best practices in data usage, helping teams build confidence and independence through consistent tools, clear examples, and shared standards.

Enable Fullscript teams to move faster by reducing dependency on specialized roles for routine data questions and by equipping them with the right resources and guidance.

Contribute to the long-term vision for analytics enablement by identifying opportunities to simplify processes, automate repetitive tasks, and enhance self-serve capabilities.

Collaborate with cross-functional partners to ensure that data solutions align with business objectives, user needs, and technical constraints.

Continuously iterate on your own work by gathering feedback, measuring adoption, and refining tools, documentation, and workflows for greater effectiveness.

Promote data literacy by creating clear pathways for teams to build the skills they need to explore data, ask better questions, and interpret results accurately.

Requirements

5+ years of experience in analytics, business intelligence, analytics engineering, data science, or a related data role.

Strong hands-on SQL skills and working proficiency in Python for data manipulation and automation.

Experience with BI and analytics tools such as Looker, Tableau, Power BI, or similar platforms for building and maintaining analytics solutions.

Experience building reusable data assets, self-serve analytics workflows, internal tooling, or reporting foundations that scale beyond ad hoc requests.

Experience teaching, training, mentoring, or enabling others to use data tools and analytics resources with more confidence and independence.

Strong communication skills and a consultative working style, with the ability to translate recurring business needs into practical, scalable solutions.

The judgment and autonomy to manage moderately complex work independently while collaborating effectively across technical and non-technical teams.

A commitment to building practical solutions that balance usability, consistency, and trust in data across the Fullscript organization.