Distributed Systems Engineer: Large-Scale Data Pipelines

Cadence Design Systems; Burnaby; On-site; CAD 89,600 - 166,400; Full time

Job summary

Cadence Design Systems in Burnaby, BC is seeking a motivated distributed systems engineer to help build scalable data processing infrastructure for massive circuit designs across distributed computing resources.

You will work on data pipelines, job orchestration, fault-tolerant scheduling, and observability, collaborating with teams to deliver production-grade infrastructure for chip design.

Qualifications

• 3+ years experience building distributed systems with Python.
• Experience with distributed computing frameworks (Dask, Spark, Ray, or Celery).
• Understanding of data locality, fault tolerance in distributed systems.
• Experience with high-performance data formats (HDF5, Parquet, Arrow).
• Familiarity with Python/C++ interop (pybind11, nanobind).
• Strong Python production code experience.
• Comfortable with large codebases and collaboration.
• Software engineering best practices (testing, code reviews).

Responsibilities

• Build data pipelines and manage I/O for large-scale netlists and simulations.
• Develop high-performance I/O for multi-TB circuit databases.
• Create Python/C++ interop layers for serialization/deserialization.
• Design streaming interfaces for distributed solver results.
• Implement distributed task distribution with fault-tolerant scheduling.
• Develop resource management and load balancing across clusters.
• Build monitoring and observability for distributed workflows.
• Optimize task granularity and dependency management.

Skills

Distributed Systems

Python

Distributed computing frameworks

Data Engineering

Python/C++ interop

Software Engineering

Code collaboration

Tools

Dask

Spark

Ray

Celery

pybind11

nanobind

Job description

Cadence Design Systems in Burnaby, BC is seeking a motivated distributed systems engineer to help build scalable data processing infrastructure for massive circuit designs across distributed computing resources.

You will work on data pipelines, job orchestration, fault-tolerant scheduling, and observability, collaborating with teams to deliver production-grade infrastructure for chip design.