Senior Data Platform Engineer

Cisco Systems, Inc; Austin (TX); On-site; USD 168,000 - 245,000; Full time

Benefits offered by this job

Medical, dental and vision insurance

401(k) matching

Paid parental leave

Restricted stock units

Job summary

Cisco Systems, Inc. is reimagining how IT infrastructure is managed through secure, cloud‑managed solutions.

The Network Platform Data Science team partners across Engineering, Product, Security, UX, Finance, Licensing, and other teams to deliver data platforms that are reliable, governed, and ready for AI to use accurately. You will set technical direction for scalable batch/streaming pipelines, define data quality and observability, and lead incident investigations to drive lasting fixes.

Qualifications

• Bachelor’s degree + 7 years of related experience, or Masters 3+ years of related experience, or PHD +1 year of related experience
• 5+ years advanced SQL including data modeling, complex transformations, and query performance tuning
• 5+ years Python building production data pipelines/services with automated testing and maintainable code
• 3+ years of Snowflake building, optimizing, and operating production data workloads (Postgres experience is a plus)
• Experience with distributed processing and orchestration (e.g., Spark and Airflow/Glue or equivalent) plus engineering practices across CI/CD, access controls, data quality, observability, incident response, or cost management.

Responsibilities

• Set technical direction for reliable, scalable batch and streaming pipelines and data products across structured and unstructured data
• Define and continuously improve expectations for data quality, freshness, availability, observability, recovery, and cost, then lead production incident investigations to deliver lasting fixes
• Build and evolve a trusted, machine-readable data context layer—covering business definitions, metric semantics, ownership, lineage, quality/freshness, and governed access integrated with existing catalog/governance systems
• Apply AI and agentic workflows to well‑scoped data engineering needs (pipeline development, validation, and bug triage), including evaluating results and using bounded permissions with human review for production‑changing actions
• Success means the organization has a trusted data foundation that scales, is observable and recoverable, reduces “definition drift,” and helps teams—including AI applications—use data accurately and confidently.

Skills

SQL

Python

Data modeling

Pipelines

Query performance

Education

Bachelor's degree

Master's degree

PhD

Tools

Snowflake

PostgreSQL

Spark

Airflow

Job description

Cisco Systems, Inc. is reimagining how IT infrastructure is managed through secure, cloud‑managed solutions.

The Network Platform Data Science team partners across Engineering, Product, Security, UX, Finance, Licensing, and other teams to deliver data platforms that are reliable, governed, and ready for AI to use accurately. You will set technical direction for scalable batch/streaming pipelines, define data quality and observability, and lead incident investigations to drive lasting fixes.