Jobs in United States

Performance Markting in United States

3,151 active opportunities · Updated October 2026

Explore current performance markting jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 Massachusetts, New York, United States· Full-time
✓ High-confidence listingCompany trend -87.2%

From $152K/yr

Quick readStrong listing-quality and freshness signals

The Manager of Networking at Datadog leads the global management of network services across all Datadog offices worldwide. This role is responsible for ensuring seamless, high-performance Wi-Fi and direct internet access in our global offices and conference room technology, supporting a rapidly growing global enterprise. As Datadog continues to grow rapidly, this role plays a critical part in scaling both the team and network infrastructure to meet increasing demand. This is a hybrid role that sits in global headquarters in New York city and requires three days in the office each week with occasional travel to our offices around the world. What You’ll Do: Lead the global network engineering teams, managing both full-time employees and third-party vendors to ensure consistent and high-quality service delivery for Datadog offices worldwide. Oversee the design, deployment and scaling of office network infrastructure, including Wi-Fi (Cisco Meraki) and edge networking devices (Cisco, Palo Alto, Juniper, and others), ensuring these services operate according to Datadog's defined service level objectives. Define and implement standards, policies, and processes for network infrastructure to ensure security, reliability and scalability. Collaborate with IT Security, Enterprise Technology, and Workplace teams to align network services with broader IT and business objectives. Develop and track operational metrics for service availability, network performance, driving continuous improvement and optimization. Who You Are: An experienced people manager with at least 5+ years of leadership experience managing teams of network engineers. Proven expertise in Wi-Fi network engineering, including deep knowledge of Cisco Meraki and edge networking solutions from vendors like Cisco, Palo Alto and Juniper. Experience managing large-scale office technology projects in global enterprises with more than 10 offices and 7,000+ employees, ensuring infrastructure keeps pace with ra

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📍 United States· Full-time
✓ High-confidence listingCompany trend -97.1%

From $151K/yr

Quick readStrong listing-quality and freshness signals

Join the MongoDB Server Query Optimization team, and help us build a world-class distributed open-source query optimizer. Our team plays a crucial role in the experience and performance of data processing. We are responsible for the MongoDB Query Language and the lifecycle of each query, through parsing, optimization and plan selection. We have a presence across the US and Europe including New York, Dublin, Seattle, Palo Alto, and Chicago. We support office-based and remote work and align projects with convenient work hours for each time zone. We have tons of interesting problems to solve with a direct impact on users for transactional, time-series, and analytical workloads. The team is endeavoring to systematically rewrite every major component of our optimization and execution systems. We need your help to design and build the heart of a distributed, flexible schema, document database. ​​This role can be based out of our US offices or remotely in the North America region. Candidate Profile 10+ years of experience in data management systems, distributed systems, or large-scale backend engineering Experience with building production-level code with a large user base, robust design structure and rigorous code quality Degree in Computer Science or similar field, or equivalent practical experience, with strong competencies in data structures, algorithms, and software design/architecture Experience with large code bases written in C++ or another systems programming language. You'll need to trace down defects, estimate work complexity, and design evolution and integration strategies as we rewrite different components of the system A strong foundation in core database internals is essential. While direct experience in query optimization is a massive bonus, it is not a prerequisite. We are also excited to meet candidates with strong backgrounds in compilers, language transpilers, or distributed storage systems Position Expectations Innovate in the area of flexible schema d

MongoDBAWSAzureRest
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📍 United States· Full-time
✓ High-confidence listingCompany trend -97.1%

From $151K/yr

Quick readStrong listing-quality and freshness signals

Join the MongoDB Server Query Execution team, and help us build a world-class distributed open-source database. Our team plays a crucial role in the performance and efficiency of MongoDB's data processing. We are responsible for building and improving the core execution engine that powers all queries, taking a logical query plan produced by the optimizer and turning it into reality. This includes developing the physical operators for data retrieval and manipulation, improving the runtime for complex analytical and transactional workloads, and owning critical components such as our new execution engine. In addition to the core server, we support the query execution needs of other major products like Atlas Streams, Atlas Search and Vector Search, and mongosync, making our work vital to the entire MongoDB ecosystem. You will be joining a globally distributed team with a significant presence in both North America and Europe. While this role is based in the NAMER region, you will regularly collaborate closely with colleagues across different time zones. We support both office-based work in our North America hubs like New York, as well as remote work. We have tons of interesting problems to solve with a direct impact on users for transactional, time-series, and analytical workloads. To meet the ever-increasing data demands of modern applications, we are actively evolving our query system; this includes strategically re-architecting and improving key components of our query execution engine. We need your help to design and build the core of a distributed, flexible schema document database. This role can be based out of one of our North America offices, such as NYC or Palo Alto, or remotely across North America. Candidate Profile 10+ years of hands-on, professional experience in query engine development or database internals Experience with building production-level code with a large user base, robust design structure and rigorous code quality Degree in Computer Science or

MongoDBAWSAzureRest
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -83.9%

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We're looking for an Optical Interconnect System Engineer to design, qualify, and deploy scalable optical connectivity for large-scale AI infrastructure. This role spans fiber-system architecture, optical-mechanical integration, validation, reliability, deployment, and serviceability. You will work with optical, mechanical, electrical, networking, manufacturing, reliability, and data-center teams to translate system needs into practical interconnect solutions. This is a hands-on role for someone who can connect design decisions with installation, qualification, troubleshooting, and long-term operational performance. In this role, you will: Define optical interconnect architectures and requirements across hardware platforms and rack-level systems. Design high-density fiber systems for performance, density, reliability, installation, and serviceability. Lead optical-mechanical integration and cross-functional design reviews. Develop test and qualification plans for optical components, modules, switching platforms, and integrated systems. Own optical loss budgets, routing guidelines, handling requirements, and serviceability criteria. Support system bring-up, deployment, troubleshooting, failure analysis, and reliability improvement. Create reusable design guidelines, interface requirements, and qualification methods. You might thrive in this role if you have: Core experience Experience desi

AWSRestAIRust
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -83.9%

ABOUT THE TEAM Critical Harm Operations sits within User Safety & Risk Operations and builds enforcement systems for Frontier Risk and Material Harm that are accurate, fast, defensible, and built to scale. The Cyber vertical turns policy into reviewer standards, calibrated judgment, quality systems, escalation paths, and automation guardrails. ABOUT THE ROLE We are looking for a senior cybersecurity practitioner and operations strategist to raise the quality, scalability, and technical rigor of our Cyber Operations. You will combine hands-on cyber judgment with systems-level operating design: resolve the hardest dual-use questions, evolve SOPs, uplift reviewers and vendors, and build practical tools and automations. This is a senior IC role. Success is not primarily cases closed; it is durable improvement in the operating model and the reviewers who run it. IN THIS ROLE, YOU WILL: Drive the Cyber Operations operating model across domain priorities, SOPs, escalation paths, quality health, vendor capability, roadmap inputs and help inform trusted access strategies. Serve as the senior cyber expert for complex or high-risk decisions across ChatGPT, API, Codex, agents, and emerging product surfaces. Translate policy ambiguity, quality misses, appeals, and reviewer disagreement into clear decision rules, calibration examples, training, and tooling requirements. Build durable operating systems and quality loops: golden sets, holdouts, double-labeling, adjudication, error taxonomies, reviewer calibration, and automation evaluations. Raise FTE and BPO capability through onboarding, certification, coaching, recurring calibration, and vendor-performance partnership. Use quality, appeals, SLA, backlog, and disagreement signals to diagnose root causes and prioritize high-leverage fixes. Build hands-on solutions—SQL analyses, scripts, dashboards, LLM eval workflows, evidence enrichment, routing logic, and lightweight automations—that improve decision quality and reduce manua

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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -83.9%

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for an experienced systems software engineer to help define and build the host software stack for our custom next-generation AI systems. You will work close to the hardware on performance-critical software, including Linux kernel drivers, high-throughput I/O paths, and system-scale networking and RDMA. This role spans architecture, implementation, platform bring-up, debugging, and performance optimization. You will work across hardware and software boundaries to make new systems usable end to end, from low-level device interfaces through userspace tooling and production validation. In this role you will: Design, implement, and debug host-side systems software for AI infrastructure, including Linux kernel drivers and supporting userspace components. Build and optimize software paths for high-throughput, low-latency communication, including RDMA and related networking functionality. Develop software around PCIe, DMA, NICs, accelerators, memory movement, and device interaction. Bring up new hardware platforms and diagnose complex issues across kernel, firmware, networking, and hardware boundaries. Build tooling for integration, testing, diagnostics, observability, qualification, and performance characterization. Collaborate with hardware, networking, and platform teams to define interfaces and integrate new capabilities. Work with external vendors where needed to integrate technologies and drive issues to resolution. Contribute across the systems sof

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Relocation support. Relocation assistance is stated. This does not establish visa sponsorship.
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -83.9%

About the Team Full Stack engineers within the Fleet Scheduling team are dedicated to building intuitive and scalable interfaces that empower researchers to efficiently manage AI workloads across some of the largest supercomputers in the world. Our focus is on developing robust, high-performance systems that provide real-time insights, resource tracking, and seamless interaction with complex infrastructure. We aim to optimize resource allocation, minimize operational overhead, and create user-friendly tools that enhance researcher productivity and system transparency. About the Role You will design, develop, and operate web-based systems that provide a powerful and intuitive interface to OpenAI’s supercomputing clusters. You will collaborate closely with researcher, product and infrastructure teams to deliver scalable solutions that enable seamless monitoring, job scheduling, and resource management. This is an opportunity to work at the cutting edge of AI infrastructure, designing tools that scale to exascale workloads while maintaining usability and performance. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design and develop full-stack web applications to track, monitor, and manage large-scale AI workloads in real time. Collaborate with researchers and infrastructure teams to translate complex operational needs into intuitive UIs and scalable backends. Build data visualization tools (e.g., Gantt charts, dashboards) to provide insights into job scheduling and resource allocation. Optimize backend services to handle massive data throughput while ensuring low-latency performance and high availability. Implement frontend components that provide seamless interactions with scheduling, storage, and compute systems. Ensure system security, reliability, and scalability across globally distributed supercomputing infrastructure. You might thrive i

PythonReactNode.jsAngular
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -83.9%

About the Team The Core Network Engineering team owns the end-to-end networking stack that connects OpenAI’s compute infrastructure — spanning global WAN/edge connectivity, data-center networking, and high-performance host/xPU networking used for large-scale training and inference workloads. This team is responsible for ensuring networking is never the bottleneck to model training efficiency, cluster reliability, or fleet expansion. They design and operate the systems that provide predictable, high-throughput, low-latency connectivity across some of the world’s most advanced AI infrastructure. About the Role We’re looking for engineers to help build and operate the networking foundation behind OpenAI’s frontier AI systems. Depending on your background and area of focus, you may work across host networking, datacenter fabrics, or global WAN infrastructure. The problems span low-level systems software, distributed infrastructure, protocol readiness, observability, performance engineering, automation, and large-scale network operations. You’ll work on systems where microseconds of latency, tail performance, and network reliability directly impact model training efficiency and production serving performance. This role is ideal for engineers who enjoy operating close to the hardware/software boundary and solving performance-critical infrastructure problems at massive scale. In this role, you will: Design, build, and operate networking systems that support large-scale AI training and inference infrastructure Improve performance, reliability, and scalability across host networking, datacenter fabrics, and WAN systems Develop automation for provisioning, configuration management, validation, upgrades, and lifecycle management of networking infrastructure Build tooling and observability systems for network health, performance analysis, debugging, and automated remediation Optimize network performance across technologies such as RDMA, RoCE, InfiniBand, Ethernet, and high-perf

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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -83.9%

AI Systems Engineer - Codex Core Agents About The Team The Codex Core Agents team builds the agent harness that turns model capability into real-world action. We own the systems around the model: prompting and interpreting model outputs, executing actions safely in real environments, and feeding production experience back into better models and better agent behavior. This team sits close to research and works across the stack: harness, model interaction, inference, sandboxed execution, orchestration, evals, production reliability, and the performance envelope around tokens, latency, cost, capacity, and quality. The harness is open source and increasingly part of how models are trained and evaluated, making this one of the highest-leverage layers in Codex. About The Role We’re looking for engineers to build the AI systems that make Codex agents dependable in production. The ideal candidate is an agent-systems builder: hands-on across low-level systems and ML workflows, able to debug Codex behavior end to end across the harness, model behavior, inference/runtime stack, GPU fleet, and product surface. You’ll work with research, infrastructure, and product to design agent harness capabilities, run experiments and ablations across the model + system prompt + harness stack, build frameworks for assessing production agent performance, and turn messy failures into durable improvements. What You’ll Do Design and build the core agent harness and execution loop that lets Codex agents interpret model outputs, use tools, execute code, and complete long-horizon tasks safely. Build sandboxing, isolation, orchestration, state, and workflow infrastructure for agents operating in real development environments. Develop evaluation, experimentation, and debugging systems that distinguish harness issues, model behavior, inference/runtime issues, and product failures. Run ablations across prompts, model-facing interfaces, context construction, tool-use strategies, and harness behavior to

PythonAWSRestAI
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -83.9%

About the Team The Workload team is responsible for designing and running OpenAI’s LLM training and inference infrastructure that powers frontier models at massive scale. Our systems unify how researchers train and serve models, abstracting away the complexity of performance, parallelism, and execution across vast GPU/accelerator fleets. By providing this foundation, the Workload team ensures that researchers can focus on advancing model capabilities while we handle the scale, efficiency, and reliability required to bring those models to life. About the Role We are looking for an engineer to design and implement the dataset infrastructure that powers OpenAI’s next-generation training stack. You will be responsible for building standardized dataset interfaces, scaling pipelines across thousands of GPUs, and proactively testing performance bottlenecks. In this role, you will collaborate closely with the multimodal researchers, and other infra groups to ensure datasets are unified, efficient, and easy to consume. In this role, you will: Design and maintain standardized dataset APIs, including for multimodal (MM) data that cannot fit in memory. Build proactive testing and scale validation pipelines for dataset loading at GPU scale. Collaborate with teammates to integrate datasets seamlessly into training and inference pipelines, ensuring smooth adoption and a great user experience. Document and maintain dataset interfaces so they are discoverable, consistent, and easy for other teams to adopt. Establish safeguards and validation systems to ensure datasets remain reproducible and unchanged once standardized. Debug and resolve performance bottlenecks in distributed dataset loading (e.g., straggler systems slowing global training). Provide visualization and inspection tools to surface errors, bugs, or bottlenecks in datasets. You might thrive in this role if you: Have strong engineering fundamentals with experience in distributed systems, data pipelines, or infrastructure.

AWSRestAIRust
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -83.9%

About the Team The Connectivity Software Engineering team is responsible for enabling seamless, secure, and high-performance wireless connectivity across OpenAI’s products. We design and optimize Bluetooth, BLE, Wi-Fi, and emerging wireless technologies to ensure robust device pairing, network performance, and interoperability. Our work spans kernel drivers, system services, and user-level tools, with a focus on real-world performance, scalability, and reliability. About the Role OpenAI is seeking a Connectivity Software Engineer to design, implement, and optimize wireless connectivity features across our product ecosystem. You’ll work at the intersection of systems software, wireless standards, and hardware integration—building robust pairing and provisioning flows, debugging low-level protocols, and driving performance under real-world RF constraints. You will also support certification, field interoperability, and fleet-scale connectivity infrastructure. This role is based in San Francisco, CA . We use a hybrid work model of 4 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, implement, and debug Bluetooth/BLE and Wi-Fi features across kernel drivers, BlueZ/wpa_supplicant/hostapd, and systemd/D-Bus services Deliver robust pairing, bonding, and provisioning flows (GATT/GAP, LE Audio/LC3, WPA3/802.1X, captive portals, NAN) Optimize link performance: throughput, latency, jitter, roaming, coexistence (BT↔Wi-Fi), and power modes (TWT, WoWLAN) Build reliable network management using NetworkManager/nmcli, nl80211/cfg80211/mac80211, DNS/DHCP/mDNS, P2P/SoftAP Instrument and analyze with packet captures and tooling (btmon/hcidump, Wireshark, iperf, eBPF/perf, spectrum sniffers) Drive interoperability and certification readiness (Bluetooth SIG, Wi-Fi Alliance) and resolve field issues with root-cause fixes Contribute to OTA-safe configuration, telemetry, and diagnostics for fleet-scale operation You might thrive in

PythonAWSLinuxRest
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -83.9%

About the Team We’re hiring software engineers to make OpenAI’s networking teams more productive. These teams build and operate the high-performance networking systems that support OpenAI’s training and inference infrastructure at frontier scale. About the Role We’re looking for someone who cares deeply about the developer experience of engineers working on complex infrastructure systems — especially around build systems, test architecture, release pipelines, and reliable development workflows. This role will be embedded with OpenAI’s networking team: making it faster, safer, and easier for engineers to build, test, validate, and ship changes across multi-server, networked, and hardware-adjacent environments. In this role you will: Improve development workflows for engineers building and operating OpenAI’s networking systems Design and improve continuous deployment, release, and validation pipelines Build and maintain test harnesses for multi-server, networked, and hardware-backed environments Improve iteration speed across C++, Python, and build-system-heavy codebases Partner with engineers to identify friction in CI, testing, debugging, and deployment workflows Drive testing and reliability strategy for infrastructure components that support large-scale training and inference workloads Work closely with centralized developer experience teams while staying deeply embedded with the networking engineers closest to the systems You might thrive in this role if: You are motivated by helping other engineers move faster and with more confidence You have experience with CI/CD, release pipelines, testing infrastructure, or build systems You are comfortable moving between C++, Python, and build systems such as CMake, Bazel, or Blaze You enjoy building test harnesses, automation, and workflow improvements for complex systems You do not need to be a networking expert, but you are excited to learn enough about the domain to make the team meaningfully more effective When you see

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Golf. A golf role or an employer dedicated to golf.
📍 Austin, Texas, United States
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

ABOUT THE BRAND: Callaway Golf Company is a premium golf equipment, gear and apparel company with a portfolio of global brands, including Callaway Golf, Odyssey, TravisMathew, and OGIO. Through an unwavering commitment to innovation and premium craftsmanship, Callaway designs, manufactures, and sells high-performance golf clubs, golf balls, apparel, bags, and other accessories—setting the standard for performance in the game of golf. Our Mission: To create demonstrably superior and pleasingly different products powered by innovative technology and premium craftsmanship enabling golfers of all abilities to play their best and find more joy in the game. Our company is a blend of experience and diverse backgrounds, and together we look to leave the past behind while moving the game forward. For more information, please visit https://www.callawaygolf.com A Customer Service Representative is responsible for managing a variety of inbound queue customer service calls representing all channels of the e-commerce CGI business, including CallawayGolf.com, CallawayGolfPreowned.com, OdysseyGolf.com, CallawayGolfVIP.com, and CallawayGolfGiftCard.com. In addition to queue customer service calls, the role will be responsible for operational order queues and consumer email from said CGI channels. ROLES AND RESPONSIBILITIES Answer incoming queue Customer Service calls. Provide exceptional consumer assistance through product knowledge and technical insight. Proactively manage operational queues through e-mail responses, call-backs, and inventory updates. Establish and maintain an influential customer service culture and provide t

Customer Service
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Golf. A golf role or an employer dedicated to golf.
📍 Cgc, Hq, United States
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

ABOUT THE BRAND: Callaway Golf Company is a premium golf equipment, gear and apparel company with a portfolio of global brands, including Callaway Golf, Odyssey, TravisMathew, and OGIO. Through an unwavering commitment to innovation and premium craftsmanship, Callaway designs, manufactures, and sells high-performance golf clubs, golf balls, apparel, bags, and other accessories—setting the standard for performance in the game of golf. Our Mission: To create demonstrably superior and pleasingly different products powered by innovative technology and premium craftsmanship enabling golfers of all abilities to play their best and find more joy in the game. Our company is a blend of experience and diverse backgrounds, and together we look to leave the past behind while moving the game forward. For more information, please visit https://www.callawaygolf.com ** 6-month contract- (Maternity Leave Coverage) ** ROLES AND RESPONSIBILITIES: In conjunction with Director, Global Soft Goods Operations, translate design concepts and briefs to finished products using knowledge of customer preferences, product functionality, materials and manufacturing techniques. Work with Product Designer to translate critical features in working designs and techpacks to communicate to suppliers. Review and negotiate specific details during the sampling process related to design specifications. Review samples for execution accuracy, product functionality, cost engineering and manufacturing efficiency. Review product costing for accuracy and potential cost savings and work with Director and Product Manager to approve final costing. Review product and material te

ExcelProject ManagementSupply Chain
CG
Golf. A golf role or an employer dedicated to golf.
📍 Cgc, Hq, United States
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

ABOUT THE BRAND: Callaway Golf Company is a premium golf equipment, gear and apparel company with a portfolio of global brands, including Callaway Golf, Odyssey, TravisMathew, and OGIO. Through an unwavering commitment to innovation and premium craftsmanship, Callaway designs, manufactures, and sells high-performance golf clubs, golf balls, apparel, bags, and other accessories—setting the standard for performance in the game of golf. Our Mission: To create demonstrably superior and pleasingly different products powered by innovative technology and premium craftsmanship enabling golfers of all abilities to play their best and find more joy in the game. Our company is a blend of experience and diverse backgrounds, and together we look to leave the past behind while moving the game forward. For more information, please visit https://www.callawaygolf.com ROLES AND RESPONSIBILITIES Drive revenue growth by identifying and enabling new programs, offerings, and fulfillment solutions, while defining and implementing the order management processes required to support new business initiatives, products, and operational capabilities. Responsible for building tools to support accurate reporting of the order book and financial reporting to identify gaps between monthly targets and plans. Monitor daily order deliveries and work directly with the Distribution Center and/or Production Managers on shipping and sales related issues. Communication and process coordination of deliveries and shipments to ensure order fulfillment within customer, sales, and company requirements are met. Develop, review, report and act on appropriate metrics associated with Sales

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