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Senior Data Engineer

  • 위치
    • Austin, Texas
  • 직무 유형 Full time
  • 게시됨
  • Job Requisition JR-202622764

설명

This role is categorized as hybrid. This means the successful candidate is expected to report to Austin Technical Center three times per week, at minimum [or other frequency dictated by the business if more than 3 days].


The Role

We are looking for a hands-on Machine Learning Engineer with at least seven years of experience to productionize machine learning for manufacturing and to build the data engineering that those models depend on. This person will design, train, validate, and deploy models, and will design and operate the ETL/ELT pipelines, feature data, and governed Bronze, Silver, and Gold products those models run on. Current, working knowledge of Databricks is required.


What You’ll Do

  • Productionize manufacturing machine learning, including training, validation, batch scoring, deployment, monitoring, and retraining workflows in Databricks.
  • Design and build the data engineering underneath those models: ingestion, transformation, curation, feature pipelines, and governed tables and volumes in Unity Catalog.
  • Build reusable Bronze, Silver, and Gold pipelines and medallion patterns that analytics and ML both consume.
  • Use MLflow and Unity Catalog for experiment tracking, model registration, versioning, lineage, and controlled promotion across environments.
  • Ingest from enterprise and plant sources with managed connectors, DLT, Auto Loader, and structured streaming where those fit.
  • Partner with data science, architecture, product, manufacturing, and platform teams using Python, Spark, SQL, and Databricks-native tools.
  • Build CI/CD for model and data products, including tests, validation gates, deployment, code review, and operational handoff.
  • Improve reliability through data validation, evaluation sets, monitoring, alerting, documentation, and runbooks.
  • Support migration from legacy and on-prem ETL, and from proof-of-concept models, into production Databricks patterns.
  • Participate in operational support and on-call rotation for production data and ML pipelines.

Your Skills & Abilities (Required Qualifications)

  • 6+ 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.
  • Proven experience deploying machine learning models into production and building the data or feature pipelines that support them.
  • Strong proficiency in Scala, Python, SQL, Spark, and Databricks, with production-quality software engineering practices.
  • Strong experience building and supporting cloud-based ETL/ELT pipelines, data platforms, and pipeline orchestration patterns for both batch and streaming operations.
  • Experience with MLflow or an equivalent model lifecycle: experiment tracking, registry, versioning, and promotion across environments.
  • Strong experience with Databricks jobs, workflows, repos, Unity Catalog, and MLflow-based experimentation and model lifecycle management.
  • CI/CD and GitHub-based deployment of data and ML products.
  • Experience delivering production pipelines with data science, architecture, product, and business partners.
  • Strong troubleshooting, communication, and technical leadership.

What Can Give You a Competitive Advantage (Preferred Qualifications)

  • Data science experience is a plus, including building and training a model, feature design, model evaluation, and working with data scientists to turn experiments into production candidates.
  • Experience deploying a model into an isolated network, such as a plant or other restricted environment, where the runtime is separated from the training platform.
  • Scala, Azure Event Hub, Kafka, or Pulsar.
  • DLT, Auto Loader, structured streaming, and metadata-driven pipeline frameworks.
  • Model monitoring, drift detection, validation gates, and production-readiness reviews.
  • Manufacturing data, plant-floor systems, industrial telemetry, or manufacturing quality use cases.
  • Legacy ETL modernization or the move from proof of concept into a governed production pattern.
  • Globally distributed teams and concurrent initiatives.

This job may be eligible for relocation benefits.


Compensation: 

  • The expected base compensation for this role is: $133,000 - $188,600. Actual base compensation within the identified range will vary based on factors relevant to the position. 
  • Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. 
  • Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, 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 and more. 

GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP NOW OR IN THE FUTURE. THIS INCLUDES DIRECT COMPANY SPONSORSHIP, ENTRY OF GM AS THE IMMIGRATION EMPLOYER OF RECORD ON A GOVERNMENT FORM, AND ANY WORK AUTHORIZATION REQUIRING A WRITTEN SUBMISSION OR OTHER IMMIGRATION SUPPORT FROM THE COMPANY (e.g., H-1B, OPT, STEM OPT, CPT, TN, J-1, etc.)


#LI-CC1

다양성 정보

General Motors는 법적으로 금지된 차별을 배제하는 것은 물론 포용성과 소속감을 진정으로 장려하는 직장이 되기 위해 노력하고 있습니다. 당사는 다양성이 보장되는 환경에서 직원들이 역량을 발휘하고 우리 고객을 위한 더 좋은 제품을 개발할 수 있다고 믿습니다. 따라서 입사에 관심 있는 사람이 있다면 포지션별 주요 업무와 자격을 확인하고 본인이 보유한 기술과 능력에 부합하는 모든 포지션에 적극적으로 지원하기를 장려합니다. 지원자는 채용 과정에서 역할 관련 평가(해당하는 경우) 및/또는 채용 전 스크리닝을 통과해야 합니다.  자세한 정보는 GM 채용 과정 안내를 참고하십시오.

공평한 취업 기회 선언 (미국)

General Motors는 공평한 기회를 제공하는 고용주임을 자부합니다.  자격을 만족하는 지원자는 인종과 피부색, 성별, 성적 지향, 성별 정체성, 국적, 장애, 재향 군인 보호법 적용 여부와 상관없이 채용 후보로서 심사를 받습니다. 

숙소 (미국 및 캐나다)

General Motors는 장애인을 포함한 모든 구직자들에게 취업 기회를 제공합니다. 구직이나 취업 지원에 도움이 되는 합리적인 숙소가 필요한 경우 [email protected]으로 이메일을 보내시거나 800-865-7580으로 전화주십시오. 이메일에, 귀하가 요청하는 특정한 숙소에 대한 설명과 귀하가 지원하는 직무와 채용 요청서 번호를 포함해주세요.