Senior C++ HPC Engineer — Distributed DB, Real-Time

BuddiesHR; United States; Hybrid; USD 114,000 - 190,000; Full time

Job summary

Circana is seeking Senior Staff Engineers to drive design, evolution, and execution of our massively parallel processing (MPP) clustered database engine that powers analytics for Circana clients in 22+ countries. You will bridge HPC and big data systems, implementing low-latency kernels on multi-core hardware and distributed networks to process terabyte/petabyte-scale datasets in real time.

You will design and optimize bare-metal software layers, contribute to architecture reviews, and mentor

Qualifications

• Bachelor's degree in CS or related field; MS preferred for senior roles.
• 8+ years production C++ and low-level systems experience.
• Strong knowledge of MPI and OpenMP for distributed computing.
• Experience with HPC and Big Data engineering and distributed engines.

Responsibilities

• Architect and design the distributed kernel and query execution engines.
• Develop and optimize high-throughput backend code in modern C++ (C++20/23).
• Plan parallel execution across many nodes using MPI and OpenMP.
• Profile, vectorize, and optimize for cache locality and SIMD intrinsics.
• Design ultra-low latency cluster communication subsystems (RDMA/ RoCE/DPDK).
• Develop in-database ML framework to minimize data movement.
• Collaborate across time zones, participate in reviews and mentoring.
• Address performance and scalability challenges across the system.

Skills

C++

Distributed systems

HPC

MPI

OpenMP

Low-latency

Performance tuning

Vectorization

Database internals

In-Database ML

Education

BS in CS or related field

MS in HPC/Big Data

Tools

MPI

OpenMP

DPDK

Valgrind

Job description

Circana is seeking Senior Staff Engineers to drive design, evolution, and execution of our massively parallel processing (MPP) clustered database engine that powers analytics for Circana clients in 22+ countries. You will bridge HPC and big data systems, implementing low-latency kernels on multi-core hardware and distributed networks to process terabyte/petabyte-scale datasets in real time.

You will design and optimize bare-metal software layers, contribute to architecture reviews, and mentor