Senior Data Engineer - Snowflake & Lang Graph AI Pipelines

Socket.dev; North Carolina; Hybrid; USD 139,000 - 204,000; Full time

Benefits offered by this job

Medical Insurance

401(k) with matching

Paid time off

Job summary

Cisco is seeking a Senior Data Engineer in the United States (hybrid). You will design and deploy data architectures, manage large-scale pipelines, and apply AI/ML techniques to optimize data workflows.

Responsibilities include building scalable data systems, ensuring data quality and security, and collaborating with data scientists to drive business outcomes using cutting-edge tools and cloud technologies.

Qualifications

• Bachelor's in Computer Science, Data Engineering, AI/ML, Data Science, or equivalent, 8+ years of related development experience, or Master's with 5+ years.
• 4+ years hands-on Data engineering on Snowflake, DBT, query optimization, data modeling and pipelines.
• Design and implement AI agent orchestration systems using Lang Graph and Lang Chain for enterprise-scale automation.
• Proficiency in SQL, Python, Java, or Scala; experience with cloud-based storage and distributed architectures.
• Experience with data validation, scrubbing, and correlation for large-scale datasets.

Responsibilities

• Data Engineering & Architecture: design scalable data architectures to store, process, and analyze high-volume datasets.
• Quality, Security, & Compliance: maintain data quality, unit tests, code reviews, and ensure data security standards.
• Collaboration & Business Impact: partner with data scientists and stakeholders to deliver actionable insights.
• Project Leadership & Strategy: lead end-to-end data projects and advise on data sources and analytics tools.

Skills

Data engineering

Snowflake

Python

SQL

ETL/ELT

Education

Bachelor's in Computer Science or related

Tools

Lang Graph

Lang Chain

Kubeflow

Job description

Cisco is seeking a Senior Data Engineer in the United States (hybrid). You will design and deploy data architectures, manage large-scale pipelines, and apply AI/ML techniques to optimize data workflows.

Responsibilities include building scalable data systems, ensuring data quality and security, and collaborating with data scientists to drive business outcomes using cutting-edge tools and cloud technologies.