BI Developer

Position Summary

The Senior Analytics Engineer owns the semantic layer architecture across one or more critical business domains and serves as the primary technical resource for BI governance and self-service analytics enablement. This role designs the data models and metrics frameworks that the business relies on daily, ensures consistency across domains, and mentors analytics engineers on best practices. The senior analytics engineer operates at the intersection of data engineering, business domain expertise, and product thinking treating every certified dataset as a data product with an SLA and a stakeholder.

Core Responsibilities

Semantic Layer Architecture

Own the design and architecture of the semantic layer across assigned domains (Finance, Operations, or Sales); ensure model consistency, reusability, and performance.

Define and enforce metric standards: canonical definitions, approved calculations, and lineage from source to report.

Lead model design reviews; establish semantic layer engineering standards for the team.

BI Platform Ownership

Own the BI platform governance model: workspace structure, certification standards, access control, and lifecycle management for reports and datasets.

Drive the transition from ad hoc reporting to governed, self-service analytics.

Evaluate and adopt new BI platform capabilities (e.g., AWS QuickSight semantic models, Copilot integration) in line with team roadmap.

Stakeholder Partnership

Serve as the senior analytics engineering partner for Finance, Operations, and Sales domain workgroups.

Translate complex business requirements into durable semantic layer designs rather than point-in-time patches.

Deliver analytics enablement training and office hours for business stakeholders.

Mentorship & Standards

Mentor Analytics Engineers through code reviews, pairing sessions, and structured design feedback.

Contribute to the analytics engineering standards playbook: naming conventions, model patterns, test coverage requirements.