Senior Analytics Engineer (Remote)

AuditBoard

7h•Remote

About The Position

As a Senior Analytics Engineer, you’ll help turn enterprise data into a platform for analytics and AI by evolving data transformation across core data marts. You’ll build and maintain models that support business decisions and enable AI-driven analysis at scale. You’ll define and implement standards for data transformation work including modeling patterns, testing and documentation so data is consistent and reusable across teams. Working closely with stakeholders, you’ll translate business questions into transformed datasets and help establish clear metrics and governance as the company grows. This role offers exposure to how the business operates, influence over how data transformation is done across the enterprise and the opportunity to build the foundation that analytics and AI experiences depend on.

Requirements

7+ years of experience in data/analytics engineering
Strong experience designing and maintaining data transformations and analytics data models using SQL and modern data stacks such as Snowflake, dbt, Python and Airflow
Demonstrated ability to define and scale transformation standards, patterns, CICD, Github Actions and SDLC practices across multiple teams
Experience supporting AI-driven analytics use cases, such as enabling semantic layers, feature-ready datasets or LLM-enabled analysis
Solid understanding of data governance classification and implementations as well as dataset certification, metric definition, ownership and data quality management
Proven ability to translate ambiguous business problems into well-structured data solutions in partnership with business teams
Comfortable identifying gaps in existing data models or processes and proposing improvements or new approaches
Strong communication skills with a track record of documenting decisions, influencing peers and driving alignment across teams
Business acumen in SaaS or technology companies, with familiarity in metrics such as ARR, churn, pipeline health, and customer lifetime value.

Responsibilities

Design and execute scalable data models and transformation patterns across core data marts that power analytics and AI use cases across the business
Partner cross-functionally to translate business problems into data solutions that support AI-led analytics and intelligent decision making
Define and drive data governance and certification standards that establish trusted, enterprise ready data sets
Define and implement SDLC best practices for data transformation, including documentation, testing and version control to ensure reliability over time
Socialise best practice guides that enable spoke analytics teams to move faster with consistent patterns
Assess existing models and pipelines to identify opportunities to simplify, standardise and improve
Identify and propose new ideas that advance an AI-led analytics experience and improve how insights are generated