layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

LAYIQ - Senior Data Engineer – Agentic AI, Automation, and Data Platforms at General Motors

Design, build, and productionize reliable, scalable, and secure data pipelines and data products in Azure Databricks that support AI, analytics, and operational use cases.
Transform raw data from multiple source systems into trusted, well-structured data products for analytics, model development, LLM applications, Vector Search, and AI agents.
Build automation and reusable engineering workflows using tools such as Cursor, Claude, LLMs, Databricks agents, and related technologies to improve development speed, testing, documentation, troubleshooting, and operational efficiency.
Design and enable governed data, retrieval, and semantic patterns for Vector Search, RAG, Databricks agents, Genie, Glean, and other AI-enabled applications.
Build and optimize batch and streaming pipelines, including feature-ready, training, inference, and model-scoring data workflows, in partnership with data science teams when needed.
Establish practical engineering patterns for CI/CD, automated testing, data quality, lineage, observability, security, cost management, and production support.
Solve complex data engineering, performance, reliability, and data-quality problems with strong ownership, urgency, and sound technical judgment.
Contribute to technical direction, reusable standards, and delivery practices across teams; influence adoption through working examples and measurable outcomes.
Mentor team members through technical guidance, design reviews, knowledge sharing, and strong engineering practices.
Your Skills & Abilities (Required Qualifications)
Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or related field, or equivalent experience.
5+ years of relevant professional experience
Strong experience in data engineering, including pipeline development, data modeling, data integration, distributed processing, and production support for enterprise data platforms.
Experience using Python or Scala, SQL, Apache Spark, and modern cloud data platforms; Azure is preferred, and AWS or GCP experience is also considered.
Experience designing, building, and optimizing scalable batch and streaming data pipelines using Databricks, Delta Lake, and medallion or comparable lakehouse architecture.
Hands-on experience using AI-assisted development or automation tools such as Cursor, Claude, GitHub Copilot, or comparable platforms to improve engineering productivity and delivery.
Hands-on experience with LLMs, Vector Search, RAG, Databricks agents, or comparable technologies used to build or enable production AI solutions.
Demonstrated ability to work independently, move quickly through ambiguity, influence technical decisions, and deliver measurable improvements in quality, reliability, efficiency, or business value.

Senior Data Engineer – Agentic AI, Automation, and Data Platforms

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