Data Analyst

General Motors•Warren, MI

2d•Hybrid

About The Position

The Infrastructure & Corporate Citizenship (ICC) team is seeking highly motivated and qualified candidates for the position of Data Analyst. This is an exciting opportunity to join a dynamic and diverse team of experienced data solutions engineers, data scientists, and analysts who design, develop, and deploy data‑driven solutions across a broad technological landscape. The team plays a critical role in driving analytics, insights strategy, data pipeline development, software integrations, and project-based solutions that support and advance ICC’s strategic objectives. In this role, you will focus on turning data into clear, actionable insights through analysis, reporting, and visualization, and you will partner closely with data scientists and solutions engineers on more advanced analytics and automation work. This position reports to the Manager, Data Analytics and Solutions Engineering.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, Engineering, Statistics, Mathematics, Business Analytics, or a related field, or equivalent experience.
5+ years of experience as a data analyst, business intelligence analyst, reporting analyst, or in a closely related analytics role working with large datasets to support business decision‑making.
Strong proficiency with SQL for querying, joining, and aggregating data from relational databases and/or cloud data platforms.
Hands‑on experience building and maintaining reports and dashboards in Power BI, Tableau, or a similar modern BI tool, including data modeling, calculations, and visual best practices.
Demonstrated ability to translate ambiguous business questions into structured analytical approaches and to deliver clear, actionable recommendations.
Familiarity with data storage solutions, databases, and data processing frameworks (e.g., data warehouses, data lakes, ETL/ELT concepts).
Strong interpersonal and communication skills, with a track record of effectively partnering with cross‑functional stakeholders and presenting findings to business partners and leadership.
High level of curiosity, attention to detail, and the ability to manage multiple tasks and projects simultaneously without sacrificing quality.

Nice To Haves

Experience working with Databricks or other cloud-based analytics platforms, including exposure to notebooks and collaborative data workflows.
Experience in facilities operations, infrastructure, construction, or real estate environments, or supporting similar operational domains with analytics.
Prior experience supporting advanced analytics and data science initiatives (e.g., working alongside data scientists on forecasting, classification, or optimization projects).
Hands-on experience with GM eSAP and Finance Core data structures (e.g., GL, cost center, project, vendor, and PO tables), translating business questions into SQL queries and curated datasets for dashboards and ad‑hoc analysis.
Familiarity with data governance concepts, including standard definitions for KPIs, data stewardship, and data quality monitoring.
Exposure to statistical analysis and experimentation (e.g., A/B testing, confidence intervals, hypothesis testing).
Experience with scripting or automation for reporting workflows (e.g., scheduling refreshes, automated data quality checks).

Responsibilities

Analyze large volumes of diverse operational, financial, and asset-related data to identify trends, patterns, and anomalies that inform business decisions and ICC strategies.
Build and maintain dashboards, reports, and self-service analytics solutions (e.g., in Power BI or Tableau) that provide clear visibility into key performance indicators and metrics for ICC stakeholders.
Perform data profiling, cleansing, and validation to ensure data quality and reliability across structured and semi‑structured sources.
Collaborate with solutions engineers to define data requirements and support the development and enhancement of data pipelines feeding ICC reporting and analytics solutions.
Translate business questions from facilities, operations, construction, corporate citizenship and real estate partners into analytical problems, and deliver structured analyses and recommendations to support decision‑making.
Present complex findings in a clear, concise way using data visualization techniques and storytelling tailored to business and technical audiences, including ICC leadership.
Document data definitions, metrics, and reporting logic to promote consistency, reuse, and a shared understanding of ICC’s data assets.
Support continuous improvement by identifying opportunities to streamline reporting processes, automate recurring analyses, and enhance existing dashboards and data products.
Partner with data scientists on exploratory analysis, feature development, and measurement plans for more advanced predictive and prescriptive models; contribute to basic statistical analysis where appropriate.
Collaborate with professionals across the enterprise, including solutions engineers, data analysts, scientists, software developers, IT personnel, and internal customers in business operations.