Senior Staff Software Engineer, C++ Distributed Systems| Hybrid: Chicago, IL

Senior Staff EngineerLet's be unstoppable together!Circana is a leading provider of technology, AI, and data solutions for consumer packaged goods companies, manufacturers, and retailers. Our predictive analytics and Liquid Data® platform help clients measure market share, uncover consumer behavior, and drive growth—powered by six decades of expertise and an expansive, high-quality data set.At Circana, we are fueled by our passion for continuous learning and growth, we seek and share feedback freely, and we celebrate victories both big and small in an environment that is flexible and accommodating to our work and personal lives. We're a global company dedicated to fostering inclusivity and belonging. We value and celebrate the unique experiences, cultures, and viewpoints that each individual brings. By embracing a wide range of backgrounds, skills, expertise, and beyond, we create a stronger, more innovative environment for our employees, clients, and communities. With us, you can always bring your full self to work. Join our inclusive, committed team to be a challenger, own outcomes, and stay curious together. Circana is proud to be Certified™ by Great Place To Work®. This prestigious award is based entirely on what current employees say about their experience working at Circana.Role OverviewWe are seeking Senior Staff Engineers to drive design, evolution, and execution of our next-generation, massively parallel processing (MPP) clustered database engine (Whitebox) that currently powers large-scale retail and consumer analytics solutions across Circana clients in 22+ countries and serving millions of queries every day in real-time against massive data sets. This is a highly technical role for an expert who bridges the gap between High-Performance Computing (HPC) and Big Data systems engineering and low-latency machine learning infrastructure and involves database internals, distributed systems, performance engineering, data processing at scale.Job ResponsibilitiesArchitecture & Design: Play a key role in core architectural choices and roadmap for our distributed database kernel, including query execution engines, custom/hybrid columnar storage layers, distributed transaction managers, and cluster coordination protocols.Low-Level Development: Write, optimize, and maintain highly performant, production-ready backend code utilizing modern C++ (C++20/23).Parallel Execution Planning: Architect MPP execution engines that distribute, schedule, and execute queries across several dozens to hundreds of nodes using MPI and hybrid OpenMP models.Hardware Optimization: Profile and eliminate execution bottlenecks by implementing explicit SIMD vectorization (AVX-512, ARM Neon, SVE) and ensuring absolute cache locality (L1/L2/L3).Distributed Memory & Networks: Design ultra-low latency cluster communication subsystems utilizing RDMA, RoCE, or kernel-bypass tech (DPDK).In-Database ML Framework Design: Architect and implement a native, highly performant, zero-copy ML execution framework directly inside the MPP engine to eliminate data serialization and transport bottlenecks between the database and external AI pipelines.Functional & High-Performance Algorithms: Develop mathematically rigorous, cache-oblivious, and highly vectorized algorithms for real-time statistical computations, matrix operations/manipulations on clustered dataVector & Embedding Infrastructure: Design and optimize or embed/reference distributed high-dimensional vector storage subsystems, custom SIMD-accelerated indexing structures (e.g., HNSW, IVF-PQ), and parallelized approximate nearest neighbor (ANN) search algorithms.Be comfortable working in a cross country/multi time zone team of elite systems engineers, implementing as well as conducting rigorous peer design and development reviewsCollaborate with cross-functional teams in defining and developing new platform capabilities.Actively participate in architecture reviews, code reviews, and technical mentoring.Investigate and resolve complex performance and scalability issues.Required Technical QualificationsMinimum - 4 years Computer Science engineering degree from a reputed institute. Masters in HPC (high performance computing) and Bigdata engineering areas preferred for Senior staff engineer and above rolesModern C++ Expertise: 8+ years of production experience writing hands-on, low-level systems in C++ (C++17/20/23 preferred). Mastery of template metaprogramming, concepts, coroutines, and custom memory allocators is key.HPC Parallelism: Very good to expert-level knowledge of cluster-scale distributed programming using MPI (Message Passing Interface) paired with shared-memory thread-level programming via OpenMP and MapReduce frameworks.Hardware-Aware Engineering: Documented experience with microarchitectural optimization, loop vectorization, pointer-aliasing constraints, and manual SIMD intrinsics programming.Concurrency Mechanics: Deep understanding of OS internals, memory barriers, lock-free data structures, and atomics (std::atomic).Database Internals: Practical experience designing core database subsystems (e.g., vectorized query operators, LSM-trees, B-trees, custom buffer pools, columnar serialization frameworks and query plan optimizers).Strong debugging, performance tuning, and problem-solving skills.Proficiency in one or more leading memory and compute monitoring/performance tools (such as Valgrind, Purify, Intel/AMD/ARM diagnostics etc.)Bonus QualificationsTrack record contributing to open-source or work experience on proprietary distributed engines (e.g., ClickHouse, DuckDB, Doris, CockroachDB, RocksDB, ScyllaDB, or Velox).Experience with cloud-native distributed, elastic environments, object storage tiering (S3/GCS), or zero-copy networking.Experience integrating heterogeneous acceleration (NVIDIA CUDA / ROCm) into big data workloads and hybrid CPU/GPU setups.Vector & Graph Algorithmic experience: Experience building or modifying high-performance vector index/search engines, graph-based indices, or localized quantization frameworks.Functional domain awareness – CPG, Retail, Pharma verticalsWhat We OfferWork on the bleeding edge of data infrastructure, tackling next gen big data engineering problems to support real time querying and analytics against some of the largest data sets at high concurrencyChallenging engineering problems - all the way from functional/data science algorithm implementations on a HPC setup to bare metal/close to OS kernel level programming involving handling of hundreds of billions of records to support real-time analytics at scale.Plenty of valuable exposure to broader BI/Analytics/Bigdata ecosystem including great opportunity to functionally better understand CPG, Retail and related domains.Highly competitive compensation package (Base, Bonus)Stimulating work environment and a great Circana work culture that allows members to bring their best daily.Circana BehaviorsBeyond technical skills, experience, and role-specific attributes, these shared behaviors are fundamental to our culture and success. We seek individuals who consistently demonstrate and champion these behaviors in their daily work:Stay Curious: Being hungry to learn and grow, always asking the big questions.Seek Clarity: Embracing complexity to create clarity and inspire action.Own the Outcome: Being accountable for decisions and taking ownership of our choices.Center on the Client: Relentlessly adding value for our customers.Be a Challenger: Never complacent, always striving for continuous improvement.Champion Inclusivity: Fostering trust in relationships engaging with empathy, respect, and integrity.Commit to each other: Contributing to making Circana a great place to work for everyone.Location: This position can be located in the following area(s): Hybrid: Chicago, ILThe below range reflects the range of possible compensation for this role at the time of this posting. We may ultimately pay more or less than the posted range. This range may be modified in the future. An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, shift, travel requirements, sales or revenue-based metrics, any collective bargaining