Sr. Analytics Engineer

Rivian•Normal, IL

5h•Hybrid

About The Position

The Senior Analytics Engineer will be a critical member of the Systems and Processes team (the "Spoke"), operating at the intersection of core business functions and centralized data assets. This role requires a highly proficient individual capable of not only consuming and transforming complex data but also understanding the why behind the business requests and translating those needs into robust analytical solutions. This role ideally will be located in Normal, IL. Ok with Atlanta, GA as well. Preferbably open to moving to Normal, IL.

Requirements

4+ years of experience in an Analytics Engineering, Business Intelligence, or Senior Data Analyst role, specifically supporting a business function (e.g., Operations, Finance, Sales).
Bachelor’s degree in Computer Science, Statistics, Mathematics, Information Systems, Economics, or a related degree
Deep SQL Proficiency: Expert-level proficiency in writing complex, highly performant SQL queries for data extraction, transformation, and modeling (CTE, window functions, complex joins).
Modern Data Platform Experience: Strong practical experience working within modern cloud data platforms such as Databricks, Snowflake, or Google BigQuery, understanding how to interact with and optimize queries against these environments.
Data Transformation Tooling: Strong practical experience with a modern data transformation framework like dbt (data build tool) for creating version-controlled, documented, and modular data models tailored for Spoke reporting needs.
Visualization Tools: Advanced skill in developing interactive dashboards and descriptive reports using leading BI tools (e.g., Tableau, Power BI, Looker).
Hub & Spoke / Domain Expertise: Proven ability to work in a federated or hub-and-spoke data model, leveraging centralized resources for localized application.
Business Acumen: Excellent understanding of Supply Chain and Logistics business processes and the ability to link analytical insights directly to operational outcomes and business strategy.
Communication: Exceptional verbal and written communication skills, with an emphasis on translating technical work for non-technical audiences.

Nice To Haves

Familiarity with Python for scripting, advanced analytics, or simple data manipulation.
Experience with data governance and documentation practices (e.g., using a data catalog).

Responsibilities

Develop and Maintain Reports and Dashboards: Build, maintain, and automate descriptive reporting, dashboards, and visualizations (e.g., Tableau, Power B, Looker) that track key performance indicators (KPIs) and operational metrics for the Supply Chain Systems and Processes domain.
Business Translation: Work directly with business stakeholders to scope analytical requests, define reporting requirements, and ensure the resulting data products accurately reflect business processes and needs.
Data Storytelling: Present complex analytical findings clearly and concisely to non-technical stakeholders, translating data into tangible business implications and recommendations for process improvement.
Data Consumption: Efficiently access, query, and utilize data assets provided by the central Data Hub (e.g., dbt models, data marts, centralized tables).
Localized Transformation: Design and implement robust, version-controlled data transformation pipelines (using SQL, Python, and/or dbt) to refine, aggregate, and model data specifically for business reporting and analytical needs.
Data Quality: Act as the first line of defense for data quality and integrity within the Business' reporting layer, collaborating with the Enterprise Data Platform team to report and resolve upstream data issues.