General Motors

General Motors

Data Engineer

Warren, Michigan, USA · Senior · full-time

No sponsorship$139k-$207kDetected 113 days ago
PythonCode ReviewGitSQLDatabricksSparkData EngineeringData ScienceAI OrchestrationCommunicationCollaborationProblem Solving

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odds of building a lasting career here

64Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

199 transfer filings in the last year, covering 199 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • This means the successful candidate is expected to report to Warren Global Technical Center, Mountain View Technical Center, or Austin Technical Center three times per week, at minimum [or other frequency dictated by the business if more than 3 days].

Responsibilities

  • Design, build, and maintain scalable data pipelines in Databricks to ingest, transform, validate, and publish trusted data products for analytics, reporting, and AI use cases.
  • Develop and support end-to-end ETL/ELT workflows using Databricks notebooks, Python, Spark, and SQL, including orchestration, parameterization, error handling, restartability, and performance optimization.
  • Build and maintain Bronze, Silver, and Gold data products that are reusable, governed, and aligned to business and downstream consumption needs.
  • Build and support integrations both into Databricks and between enterprise applications, including legacy and modern integration patterns such as DataStage-based workflows.
  • Implement pipeline logic for ingestion, standardization, cleansing, enrichment, joins, aggregations, and publishing of curated data assets for downstream use.
  • Partner with product owners, architects, source-system teams, report and analytics teams, and data consumers to translate business needs into well-defined technical solutions and trusted data products.
  • Define and implement data transformations, semantic structures, and curated data assets that improve usability, consistency, downstream performance, and trust in the data.
  • Support secure and compliant data delivery by implementing access controls, permissions, and governance requirements in alignment with GM policies.
  • Contribute to team standards, reusable patterns, and best practices for notebooks, Python development, GitHub workflows, data engineering, integration design, data quality, and operational support.
  • Strong knowledge of data warehousing and ETL/ELT concepts, including how upstream design impacts downstream performance, usability, and trust in data products.

Requirements

  • Experience with secure data delivery, access controls, and enterprise governance standards.
  • Experience with production support, observability, and operational reporting for data platforms.

Nice to have

  • Apply strong data quality, validation, reconciliation, and documentation practices to ensure data products are accurate, discoverable, reliable, and production-ready.
  • Use GitHub-based development practices for version control, code review, collaboration, and promotion of pipeline changes across environments.
  • Help modernize legacy integrations and reporting patterns by standardizing and migrating solutions onto the enterprise data platform.
  • Your Skills & Abilities (Required Qualifications) Bachelor's degree in Computer Science, Information Systems, Data Engineering, Data Science, Engineering, or a related field
  • or equivalent experience.
  • 5+ years of experience as a data engineer, ETL developer, or integration engineer building production-grade data pipelines and data products.

Compensation

  • The expected base compensation for this role is: $138,700 - $206,950.
  • 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.
  • Benefits Overview From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions.
  • Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.
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This listing is sourced directly from General Motors's careers page and normalized into a canonical job model.