Senior Data Engineer

General Motors; Nacogdoches (TX); Hybrid; USD 119,000 - 175,000; Full time

Benefits offered by this job

Health benefits

GM vehicle discounts

Tuition assistance

Paid time off

Job summary

General Motors is seeking a hands-on Senior Data Engineer in Texas to design, build, and productionize secure, scalable data pipelines for telematics data. Hybrid work with three days onsite at Warren or Austin centers.

You will enable GenAI-ready datasets, governance, and reusable data products to accelerate analytics across the enterprise. Applicants should have 5+ years in data/software engineering, deep experience in Spark, Databricks, Delta Lake, and Python/Scala, plus cloud platforms and

Qualifications

• Bachelor's degree or equivalent experience in computer science, software engineering, data science, or a related field.
• 5+ years of data engineering or software engineering experience.
• Experience supporting AI/ML through feature engineering, model-ready data, or deployment.
• Experience building GenAI, retrieval-augmented generation or self-service data tools.
• Experience with cloud data services (Azure, AWS, or GCP) and data orchestration tooling.

Responsibilities

• Design, build, and productionize secure, scalable batch and streaming data pipelines.
• Transform data from multiple sources into trusted analytics-ready datasets.
• Develop ETL/ELT workflows using Spark, Delta Lake, and medallion architecture.
• Enable self-service analytics and GenAI through governed data products and APIs.
• Mentor engineers and contribute to engineering standards and documentation.

Skills

Python

Scala

Databricks

Apache Spark

Delta Lake

SQL

Education

Bachelor's degree in CS/related field

Tools

Azure Databricks

AWS EMR

Kubernetes

Job description

Job Description This role is categorized as hybrid. This means the successful candidate is expected to report to Warren Global Technical Center or Austin Technical Center three times per week, at minimum [or other frequency dictated by the business if more than 3 days]. The Role We're looking for a hands‑on Senior Data Engineer to build the next generation of telematics data products that power analytics, artificial intelligence, and decision‑making across the enterprise. This role is about creating trusted, reusable, analytics‑ready data products that make complex telemetry data easier to discover, understand, and use at scale. You'll help move the organization from custom analytics and duplicated logic toward standardized, reusable data products that deliver consistent value across teams. You'll help define foundational datasets, shared metrics, and curated data products that enable teams across engineering, product, quality, safety, and operations to unlock the value of connected vehicle data. Your work will help establish a trusted, common data foundation for connected vehicle insights. By replacing duplicated analytical logic with reusable, governed data products, you'll improve consistency, increase adoption, and accelerate analytics, machine learning, and AI use cases across the enterprise. You'll make complex telemetry data easier to discover, understand, and use—helping teams move faster from raw signals to confident decisions about product quality, vehicle performance, safety, and operations.

What You’ll Do

• Design, build, and productionize secure, scalable batch and streaming data pipelines in Azure Databricks and cloud environments.
• Transform data from multiple source systems into trusted, well‑structured datasets for analytics, AI, machine learning, and operational use cases.
• Develop and optimize ETL/ELT workflows using Apache Spark, Delta Lake, and medallion architecture.
• Enable self‑service analytics and GenAI use cases through governed data products, reusable APIs, semantic layers, and trusted data services.
• Enable AI and data science workflows through feature‑ready and model‑ready datasets, curated context for GenAI applications, experimentation support, and repeatable delivery patterns.
• Implement data quality, lineage, monitoring, validation, access controls, and privacy practices to ensure reliable and compliant data products.
• Improve engineering processes, automation, delivery patterns, platform performance, scalability, and cost efficiency.
• Partner with data scientists, analysts, software engineers, product teams, and business stakeholders to deliver measurable business outcomes.
• Troubleshoot production issues, resolve root causes, and maintain reliable data platform operations.
• Contribute to engineering standards, reusable frameworks, technical documentation, and a culture of data product thinking.
• Influence technical direction, mentor engineers, document solutions, and promote strong engineering practices.

Your Skills & Abilities (Required Qualifications)

• Bachelor’s degree in computer science, software engineering, data science, or a related field, or equivalent experience.
• 5+ years of relevant experience in data engineering, software engineering, or a related discipline.
• Experience supporting AI or machine learning through feature engineering, model‑ready data, experimentation workflows, or model deployment.
• Experience building GenAI, retrieval‑augmented generation, natural‑language analytics, or self‑service data tools.
• Experience with cloud data services such as Azure Data Lake, Azure Kubernetes Service, AWS EMR, or comparable technologies.
• Experience with workflow orchestration, CI/CD, infrastructure as code, automated testing, and data observability.
• Strong experience with enterprise data pipelines, data modeling, data integration, and production support.
• Proficiency in Python or Scala, advanced SQL, and Unix/Linux.
• Hands‑on experience with Databricks, Apache Spark, Delta Lake, and distributed data processing.
• Experience with relational, key‑value, document, or other NoSQL data stores.
• Experience designing data solutions on Azure; AWS or GCP experience is also applicable.
• Knowledge of batch and streaming architectures, cloud platforms, Kubernetes, and distributed systems.
• Experience with data formats such as JSON, Parquet, Avro, and XML.
• Understanding of data governance, privacy, security, data quality, and responsible AI practices.
• Ability to work independently, solve complex problems, manage competing priorities, and communicate technical concepts clearly.

What Can Give You a Competitive Advantage (Preferred Qualifications)

• Master’s degree in computer science, software engineering, data science, or a related field.
• Experience with data catalogs, metadata management, lineage, and governance platforms such as Atlan, Collibra, or Alation.
• Demonstrated technical leadership, mentoring, cross‑functional collaboration, and process improvement impact.

Compensation

The expected base compensation for this role is: $119,200 - $175,450. Actual base compensation within the identified range will vary based on factors relevant to the position.

BonusPotential

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.)

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