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Senior Quality Data Engineer, AI
General Motors. Develop and productionize reliable batch and streaming data products in Azure Databricks .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and productionizing data products using Azure Databricks, with strong proficiency in SQL, Python, and PySpark. Capable of building scalable data pipelines and responsive front-end applications while ensuring data quality and security.
Highest-signal resume keywords
Azure DatabricksSQLPythonReactETL/ELT Pipelines
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
SQLPythonPySparkScalaJavaETL/ELT PipelinesData ModelingData QualityDistributed ProcessingAI Tools
Soft Skills
Strong CommunicationProblem-Solving
Tools & Technologies
DatabricksREST APIsDelta LakeUnity CatalogSpark Declarative Pipelines
Industry Keywords
Data EngineeringSoftware EngineeringData WarehousesData LakesLakehouse Platforms
Tech Stack
Tools & technologiesAzureCloudETLJavaJavaScriptPySparkPythonReactScalaSparkSQLTypeScriptUnity
About the role
Key responsibilities & impact- Develop and productionize reliable batch and streaming data products in Azure Databricks
- Use Spark Declarative Pipelines, Delta Lake, Unity Catalog, and Bronze, Silver, and Gold data patterns
- Identify opportunities to apply AI across data workflows
- Build and maintain data services and APIs that securely expose trusted, documented data
- Develop responsive front-end features using React, JavaScript or TypeScript, and modern web development practices
- Collaborate with product designers and stakeholders to translate workflows and data needs into usable interfaces
- Establish data quality checks, observability, lineage, and alerting
- Investigate and resolve pipeline and application issues
- Improve performance, reliability, security, and cost efficiency across data and application systems
- Apply code review, automated testing, CI/CD, workload identity, security, cost, observability, and production support practices
- Gate agent releases by evaluating task success, tool use, grounding, latency, and cost
- Mentor engineers and provide technical guidance
- Contribute to roadmaps and architectural decisions
Requirements
What you’ll need- 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 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 to improve data engineering workflows, with an understanding of responsible and secure AI use
- Hands-on experience building or maintaining front-end applications with React
- Familiarity with component-based UI patterns
- Experience integrating front-end applications with REST or similar APIs
- Experience handling asynchronous data states, errors, and loading behavior
- Understanding of data modeling, schema evolution, data quality, and distributed processing concepts
- Strong experience with Databricks on a cloud platform, building and supporting scalable data pipelines
- Strong communication and problem-solving skills, with the ability to work across technical and nontechnical teams
- Must not require GM immigration sponsorship now or in the future
Benefits
Comp & perks- Relocation benefits may be available
- Medical insurance
- Dental insurance
- Vision insurance
- Health Savings Account
- Flexible Spending Accounts
- Retirement savings plan
- Sickness and accident benefits
- Life insurance
- Paid vacation and holidays
- Tuition assistance programs
- Employee assistance program
- GM vehicle discounts
- Bonus/incentive pay program based on company, job-level, and individual performance