Staff C++ Distributed Systems Engineer - Remote

BuddiesHR; Chicago (IL); Hybrid; USD 140,000 - 170,000; Full time

Benefits offered by this job

Paid time off

Medical/dental/vision insurance

401(k) retirement plan

Bonus pay eligible

Job summary

Circana is seeking a Staff Software Engineer to advance a massively parallel, distributed database engine (Whitebox) powering real-time analytics at scale. You will craft high-performance C++ kernels, exploit SIMD, and optimize across HPC and big data domains in a hybrid Chicago, IL environment.

You will collaborate with cross-functional teams to shape architecture, implement low-latency kernels, and drive performance improvements across terabyte/petabyte-scale datasets used by Circana clients

Qualifications

• Bachelors degree in CS; Masters preferred for senior roles.
• 6+ years of production C++ experience (C++17/20/23).
• Strong HPC/BigData background with MPI + OpenMP.
• Experience in design of high-performance database or data systems.

Responsibilities

• Architect and drive distributed database kernel design and roadmap.
• Develop low-latency, high-throughput backend code in C++.
• Design and implement MPI/OpenMP based parallel execution planning.
• Profile and optimize with SIMD intrinsics for performance.
• Design low-latency cluster communications (RDMA/DPDK).
• Develop in-database ML framework and vector data support.
• Participate in architecture reviews and mentoring.

Skills

C++ development

HPC

Distributed systems

Low-latency design

Performance tuning

Problem solving

OS internals

Education

Bachelor's degree in CS or equivalent

Master's in HPC/Big Data (preferred)

Tools

MPI

OpenMP

SIMD intrinsics

Vectorization

Job description

Circana is seeking a Staff Software Engineer to advance a massively parallel, distributed database engine (Whitebox) powering real-time analytics at scale. You will craft high-performance C++ kernels, exploit SIMD, and optimize across HPC and big data domains in a hybrid Chicago, IL environment.

You will collaborate with cross-functional teams to shape architecture, implement low-latency kernels, and drive performance improvements across terabyte/petabyte-scale datasets used by Circana clients