Senior Data Engineer: Anomaly Detection & Dashboards

General Motors; Warren (MI); Hybride; USD 125 000 - 169 000; Plein temps

Avantages offerts par ce poste

Health and wellbeing benefit programs

Health Savings Account

Flexible Spending Accounts

Retirement savings plan

Sickness and accident benefits

Life insurance

Paid vacation & holidays

Tuition assistance programs

Employee assistance program

GM vehicle discounts

Bonus Potential

Résumé du poste

General Motors in Warren, MI seeks a senior analytics engineer to build and operationalize analytics and anomaly detection that improve vehicle, software, and product-quality outcomes.

You will collaborate with subject matter experts to define metrics, thresholds, and decision criteria; run unbiased analyses across vehicle, software, warranty, diagnostic, fleet, and product-quality data; deploy anomaly-detection solutions and end-to-end pipelines.

Qualifications

• Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, or related field, or equivalent practical experience.
• 7+ years of data engineering/development or related experience.
• Experience applying statistical analysis and/or ML methods (anomaly detection, forecasting, classification) to real-world problems.
• Strong Python skills for data analysis, algorithm development, automation, and production workflows.
• Experience querying, transforming, validating, and analyzing large datasets using SQL and modern data technologies.
• Ability to take an analytical solution from problem definition through testing, deployment, monitoring, and improvement.
• Experience communicating analytical results to stakeholders with varying technical expertise.
• Strong data-quality mindset and ownership, with ability to deliver in cross-functional teams.

Responsabilités

• Collaborate with subject matter experts to define metrics, analytical objectives, thresholds, and decision criteria.
• Run unbiased analyses to uncover trends, anomalies, relationships, and risks across vehicle, software, warranty, diagnostic, fleet, and product-quality data.
• Design, test, and deploy anomaly-detection and monitoring algorithms for issues impacting customers.
• Build end-to-end analytical pipelines delivering insights, dashboards, alerts, and operational workflows from raw data.
• Create alerting solutions for rapid response to high-priority vehicle and product issues.
• Establish validation methods using historical data, testing, domain expertise, and real-world observations.
• Communicate findings and recommendations to technical and non-technical audiences.
• Improve performance, scalability, and cost efficiency through model, query, pipeline, and architecture improvements.
• Standardize analytical processes and adopt modern Azure-based technologies to reduce data handling complexity.
• Support launches with readiness insights and analytical tools.
• Document methods, data lineage, operating procedures, and known limitations for maintainability.

Connaissances

Python

SQL

Azure

Databricks

Data pipelines

Git-based workflows

Formation

Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, or related field

Equivalent practical experience

Outils

Azure Data Factory

Databricks

Git

CI/CD

Databricks Asset Bundles

Description du poste

General Motors in Warren, MI seeks a senior analytics engineer to build and operationalize analytics and anomaly detection that improve vehicle, software, and product-quality outcomes.

You will collaborate with subject matter experts to define metrics, thresholds, and decision criteria; run unbiased analyses across vehicle, software, warranty, diagnostic, fleet, and product-quality data; deploy anomaly-detection solutions and end-to-end pipelines.