Senior Data Engineer
General Motors6 days ago
Base Salary
$133k - $189k/yr
Responsibilities
- Productionize manufacturing machine learning through training, validation, batch scoring, deployment, monitoring, and retraining workflows.
- Design and operate ingestion, transformation, curation, feature, ETL/ELT, and governed Bronze, Silver, and Gold data pipelines.
- Use Databricks, Unity Catalog, and MLflow for data governance, experiment tracking, model registration, versioning, lineage, and controlled promotion.
- Build batch and streaming pipelines using managed connectors, DLT, Auto Loader, and structured streaming where appropriate.
- Develop CI/CD, testing, validation gates, deployment workflows, documentation, runbooks, monitoring, alerting, and operational handoff for data and ML products.
- Support migration from legacy and on-premises ETL and proof-of-concept models into governed production Databricks patterns.
- Partner with data science, architecture, product, manufacturing, platform, and business teams, and participate in production support and on-call rotation.
Requirements
- At least six years of experience in machine learning engineering, data engineering, or both.
- Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field, or equivalent experience.
- Experience deploying machine learning models into production and building the supporting data or feature pipelines.
- Strong proficiency in Scala, Python, SQL, Spark, and Databricks.
- Strong experience building and supporting cloud-based ETL/ELT pipelines, data platforms, and orchestration patterns for batch and streaming operations.
- Experience with MLflow or an equivalent model lifecycle covering experiment tracking, registry, versioning, and environment promotion.
- Experience with Databricks jobs, workflows, repos, Unity Catalog, MLflow experimentation, and model lifecycle management.
- Experience with CI/CD and GitHub-based deployment of data and ML products.
- Experience delivering production pipelines with cross-functional data science, architecture, product, and business partners.
- Preferred qualifications include data science and model training experience, isolated-network deployments, Azure Event Hub, Kafka, Pulsar, DLT, Auto Loader, structured streaming, metadata-driven frameworks, model monitoring, drift detection, manufacturing data, industrial telemetry, legacy ETL modernization, and globally distributed teams.
Benefits
- Hybrid work requiring attendance at the Austin Technical Center at least three times per week, or more frequently if dictated by the business.
- The role may be eligible for relocation benefits.
- Benefits include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings, sickness and accident benefits, life insurance, paid vacation and holidays, tuition assistance, employee assistance programs, and GM vehicle discounts.
Tech Stack
Categories
Data EngineeringML Engineering
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.