Senior Data Engineer: AI Pipelines & Data Governance

IBM; Austin (TX); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Remote-friendly

Competitive salary

IBM culture

Job summary

IBM Consulting is seeking an experienced Data Engineer to design, scale, and govern data pipelines and infrastructure for AI-enabled engagements. You will collaborate with AI architects to ensure data reaches the right systems in the right form across modern platforms.

You will build robust pipelines using Microsoft Fabric, Databricks, and Azure Synapse, while implementing governance, lineage, and secure data access.

Qualifications

• Master's degree required in a related field.
• 7+ years designing, developing, and deploying scalable AI apps.
• Experience with LLMs, RAG, and agentic AI workflows.
• Strong data governance, lineage, and security awareness.
• Proficient in AI orchestration pipelines and MLOps patterns.
• Experience integrating AI with enterprise data platforms and APIs.
• Knowledge of CI/CD pipelines for AI deployments.

Responsibilities

• Design, build, and scale data pipelines ingesting and delivering high-quality data.
• Architect and maintain data infrastructure to support AI and analytics use cases.
• Implement data quality checks, governance, and lineage tracking across platforms.
• Collaborate with AI engineers to ensure data outputs suit model consumption and dashboards.

Skills

AI design

Data pipelines

Cloud data platforms

LLMs

RAG

Agentic AI

CI/CD

Education

Master's Degree in CS/Engineering

Master's Degree

Tools

LangChain

LangGraph

AutoGen

Semantic Kernel

CrewAI

Databricks

Pinecone

Weaviate

Job description

IBM Consulting is seeking an experienced Data Engineer to design, scale, and govern data pipelines and infrastructure for AI-enabled engagements. You will collaborate with AI architects to ensure data reaches the right systems in the right form across modern platforms.

You will build robust pipelines using Microsoft Fabric, Databricks, and Azure Synapse, while implementing governance, lineage, and secure data access.