Senior Quality Data and AI Engineer
General Motors2 days ago
Base Salary
$125k - $169k/yr
Responsibilities
- Develop and productionize batch and streaming data products in Azure Databricks using Spark Declarative Pipelines, Delta Lake, Unity Catalog, and Bronze, Silver, and Gold data patterns.
- Identify and deliver AI applications across data workflows to improve efficiency, quality, and decision-making.
- Build and maintain secure, documented data services and APIs for application consumption.
- Develop responsive React front-end features using JavaScript or TypeScript and integrate them with APIs.
- Establish data quality checks, observability, lineage, alerting, automated testing, CI/CD, workload identity, and production support.
- Improve performance, reliability, security, and cost efficiency across data and application systems.
- Evaluate agent releases for task success, tool use, grounding, latency, and cost.
- Mentor engineers, provide technical guidance, and contribute to roadmaps and architecture decisions.
Requirements
- 5+ years of professional experience in data engineering, software engineering, or a closely related field.
- Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field, or equivalent experience.
- Strong proficiency in SQL, Python, PySpark, and a data-engineering language such as Scala or Java.
- Experience designing production-grade ETL/ELT pipelines and working with data warehouses, data lakes, or lakehouse platforms.
- Practical experience using AI tools and services in data engineering workflows with responsible and secure AI practices.
- Hands-on experience building or maintaining React front-end applications and integrating them with REST or similar APIs.
- Understanding of data modeling, schema evolution, data quality, and distributed processing.
- Strong experience with Databricks on a cloud platform and scalable data pipeline development and support.
- Preferred qualifications include Apache Spark, Kafka, Airflow, Snowflake, BigQuery, Redshift, Docker, Kubernetes, infrastructure as code, cloud-native architectures, front-end testing, accessibility, design systems, authentication, authorization, secure sensitive-data handling, mentoring, and cross-team delivery.
- Strong communication and problem-solving skills across technical and nontechnical teams.
Benefits
- Hybrid work requires reporting to the Austin Technical Center at least three times per week, or more frequently if business needs dictate.
- The role may be eligible for relocation benefits.
- GM offers medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings, sickness and accident benefits, life insurance, paid vacation and holidays, tuition assistance, an employee assistance program, and GM vehicle discounts.
Tech Stack
Amazon RedshiftApache AirflowApache KafkaApache SparkDatabricksDockerGoogle BigQueryJavaJavaScriptKubernetesPythonReactScalaSnowflakeSQLTypeScript
Categories
Data EngineeringFull Stack
About General Motors
General Motors designs, manufactures, and sells cars, trucks, and electric vehicles for consumers and commercial fleets under brands including Chevrolet, GMC, Cadillac, and Buick. A public company on the NYSE headquartered in Detroit and founded in 1908, it operates globally and is developing EVs on its Ultium battery platform. Revenue comes from vehicle and parts sales, connected services such as OnStar, and financing through GM Financial.