External Data Specialist Jobs

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for a Director of Data Engineering to join our team. This is a Hybrid (Ramat Gan) role, reporting to the VP Engineering - Lakehouse in the Exposure Management & Security Operations department. In this role, you will lead multiple data engineering teams driving the strategy, architecture, and operation of a high-scale, multi-tenant cybersecurity data platform. What you’ll do (Role Expectations) Manage and mentor engineering managers and technical leads while aligning platform strategy with company goals and cross-functional partners Engineer, maintain, and scale core data pipelines and data platform infrastructure, designing reliable ETL and ELT flows across databases, APIs, event streams, business systems, and data lakes Oversee platform reliability, cost optimization, CI/CD pipelines, and enterprise-grade observability Build scalable data solutions for internal teams as well as external, user

Join the team shaping the future of AI at Scale. Scale builds RL environments: sandboxed replicas of the digital spheres where real knowledge work occurs and built from the operating data of the companies that actually hold it. As the Data Acquisition Lead , you will own the commercial motion that gets us that data end to end. You will figure out which companies sit on the data for the next domain worth owning and then go and get it. This is a zero-to-one function with no playbook. You should be prepared to wear many hats, from thesis-driven dealmaker to hands-on operator to technical translator between commercial and Research teams. You will: Map the supply side. Work backwards from where labs are pushing to the specific organizations holding the underlying data. Build a thesis on which domains are worth owning and in what order. Invent the deal structures. You'll work with Scale’s legal team to define the first version of how these transactions get priced. Close. Own it from cold outreach to signature. Close the loop with the technical side. You need to hold a real conversation about what makes a dataset trainable and become an expert in what makes this underlying data valuable. Build the machine. Do the work by hand first, then turn what you learn into a repeatable pipeline. Ideally, you’d have: 5+ years across some mix of business development, corp dev, commercial strategy, or early-stage GTM. The label matters less than a track record of building a commercial motion that didn't exist before you got there A strong track record of managing important external relationships Strong business judgment and the ability to evaluate partnership value quickly Clear communication skills and comfort working with senior stakeholders Ability to operate independently while staying closely connected to cross-functional teams A practical, hands-on approach to building new functions from the ground up Comfort working in fast-moving, ambiguous environments Experience in

About the team The Monetization Data Platform team builds the trusted data and platform foundations that power how the company develops, measures, and improves monetization products. We bring together product usage, pricing, billing, ads, payments, and financial data to help Product, Engineering, Finance, and GTM teams make better decisions and deliver reliable customer experiences. We work at the intersection of data engineering, product engineering, platform engineering, Finance, and GTM. Our goal is to turn complex monetization and financial data into accurate, explainable, and timely data products while building systems that scale with the growth and complexity of the business. About the role We are looking for a Data Engineer to improve and build the next generation of our monetization data platform. You will own high-impact systems end to end, from product instrumentation, source ingestion, and canonical modeling through quality controls, observability, and delivery to downstream consumers. This is a hands-on role for an engineer who enjoys solving ambiguous product and data problems, designing durable architectures, and partnering closely with Product Engineering, Finance, Accounting, and GTM. You will help define technical direction, raise the engineering bar, and turn monetization opportunities into trusted, scalable data products and platform capabilities. In this role, you will Design, build, and operate large streaming and batch data pipelines that process product, financial, and operational data from a variety of internal and external systems. Develop canonical data models and reusable data products for domains such as product usage, pricing, billing, ads, payments, revenue, and the general ledger. Establish strong guarantees for data accuracy, completeness, freshness, lineage, reconciliation, and auditability. Build frameworks and platform capabilities that improve developer productivity and make it easier for teams to launch, measure, and iterate on m

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Training and serving frontier AI models requires compute infrastructure at a scale and density that pushes past what conventional data center designs were built to handle. Anthropic’s Data Center team is responsible for delivering that physical infrastructure — partnering with build partners, equipment manufacturers, and vendors to stand up facilities that can reliably cool some of the largest accelerator clusters in the industry. As a Senior Data Center Mechanical Engineer based in the United States, you’ll lead the design direction and technical oversight of building mechanical systems — cooling, chilled-water distribution, liquid cooling, plumbing, and fire protection — across our rapidly expanding U.S. portfolio. This is a senior individual contributor role focused on driving and reviewing mechanical design from concept through detailed design and construction documentation produced by external engineering firms and development partners, ensuring every facility meets Anthropic’s standards for reliability, efficiency, and scalability. You’ll own the mechanical design direction from Basis of Design through construction and commissioning, serving as the primary technical interface between Anthropic’s internal teams and our external engineering and development partners. A central part of this role is speed-to-capacity through prefabrication and modular construction — modular cooling skids, prefabricated piping assemblies, and design for offsite manufacture that compress schedules and reduce onsite labor. You’ll bring deep familiarity with U.S. mechanical, plumbing, and fire codes and the local regulatory environment, an

About the Team The Human Data team turns human feedback into reliable signals for training and evaluation. We design and run end-to-end programs that capture the depth of human intent behind everyday and high-stakes uses of our models. Our remit spans bespoke data campaigns, scalable synthetic data generation, and product-embedded signals. We partner closely across all research teams to translate these signals into training datasets, novel evaluations, and feedback loops that push the frontier of our models and advance their applications. About the Role As a Program Manager (PGM) in the Human Data team you will partner with our research teams, operations and engineering to execute complex programs for collecting high-quality data. You will be a key interface between our external vendors and AI trainers, ensuring human data campaigns are successfully completed. Your work will play a key role in enabling OpenAI to train safe models that will land in the real world This role is based in our San Francisco HQ. In this role, you will: Work in a high velocity environment, where the outcome of your work will have a direct impact on the models that OpenAI deploy in the real world Work closely with external vendors, trainers and internal researchers to collect, review, and deliver high-quality data Gather requirements, write instructions, define success criteria, and calibrate the AI trainers Use internal tooling to assess labeled data and provide feedback to AI trainers Think critically and share recommendations on tooling and process improvements, optimizing for quality, throughput, and AI trainer experience You’ll thrive in this role if: You thrive in dynamic environments. You are comfortable navigating ambiguity, managing shifting priorities, and adapting to fast-paced changes without missing a beat. You’re curious about AI, LLMs, Agents. While not required, an interest or background in these areas will help you connect the dots in our broader mission. You have a can-do a

About the Team OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. This team is central to this mission, setting the core infra strategy and implementing this vision. From site selection to the buildout process, this team sits at the intersection of commercial, technical, strategy, and operations, interacting with teams and executives inside and outside of OpenAI. About the Role We are seeking experienced Data Center Mechanical and Electrical/Power Design Engineers with expertise in designing, operating, and maintaining large-scale data center campuses. The ideal candidate for this role will have extensive background and experience in design and managing critical equipment and facilities, design and operation of MEP (Mechanical, Electrical, Plumbing) systems, and overseeing operational activities from initial phases of Data Center build through delivery and ongoing maintenance. The ideal candidate will have a strong technical background, operational leadership experience, and a proven ability to collaborate with external vendors on critical infrastructure. This role offers the opportunity to lead transformative data center projects with high visibility and impact. If you are passionate about delivering cutting-edge infrastructure solutions, we encourage you to apply. Key Responsibilities Oversee building and MEP design, operation, and maintenance, including reviewing building and MEP drawings and proposals across all project phases. Lead operational activities for large-scale data center campuses, from early design phases through delivery and daily operation. Operate and maintain critical data center facilities and equipment, ensuring reliability and performance. Collaborate with external vendors to select, procure, and manage critical equipment, such as generators, UPS, chillers, and CDUs. Provide technical expertise on all aspects of data center building, equipment, and

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data is at the heart of Lyft Business's products and decision-making. We're looking to hire a Data Analyst to build the tools and analytics that drive revenue for the sales organization behind Lyft's B2B portfolio — a multi-billion-dollar book of business spanning healthcare, business travel, corporate commute, automotive, and transit. This team has real say in what gets built. You will be the analytical partner to our Sales and account teams — someone who can translate findings into a clear narrative for both technical and non-technical audiences. Responsibilities: Build the tools and analytics sales leaders use to grow their accounts — pacing views, account-health signals, territory and segment views that change what a rep or manager does next Field requests from Sales, Product, Finance, Legal, leadership, and external stakeholders, and decide what's worth building, what's worth a sharp piece of analysis, and what's out of scope Build and maintain production data pipelines, and automate recurring workflows, with documentation and validation clear enough that a teammate — or an AI agent — can use them without asking you first Define what the team's core metrics mean and where they live, so every dashboard, report, and tool returns the same answer to the same question Contribute to the internal tools and semantic layer — prompts, context, and guardrails — that let stakeholders query B2B data in natural language and trust what comes back Translate insights into a cohesive narrative and present technical findings to senior leadership and non-technical audiences Experience: Degree (or related work experience) with a focus in analytics, statistics, economics, computer science, or other quantitative fields 3+ years of experience in a data analytics or business intelligence role, ideally supporting a sales

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data is at the heart of Lyft Business's products and decision-making. We're looking to hire a Data Analyst to build the tools and analytics that drive revenue for the sales organization behind Lyft's B2B portfolio — a multi-billion-dollar book of business spanning healthcare, business travel, corporate commute, automotive, and transit. This team has real say in what gets built. You will be the analytical partner to our Sales and account teams — someone who can translate findings into a clear narrative for both technical and non-technical audiences. Responsibilities: Build the tools and analytics sales leaders use to grow their accounts — pacing views, account-health signals, territory and segment views that change what a rep or manager does next Field requests from Sales, Product, Finance, Legal, leadership, and external stakeholders, and decide what's worth building, what's worth a sharp piece of analysis, and what's out of scope Build and maintain production data pipelines, and automate recurring workflows, with documentation and validation clear enough that a teammate — or an AI agent — can use them without asking you first Define what the team's core metrics mean and where they live, so every dashboard, report, and tool returns the same answer to the same question Contribute to the internal tools and semantic layer — prompts, context, and guardrails — that let stakeholders query B2B data in natural language and trust what comes back Translate insights into a cohesive narrative and present technical findings to senior leadership and non-technical audiences Experience: Degree (or related work experience) with a focus in analytics, statistics, economics, computer science, or other quantitative fields 3+ years of experience in a data analytics or business intelligence role, ideally supporting a sales

About the Team OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. This team is central to this mission, setting the core infra strategy and implementing this vision. From site selection to the buildout process, this team sits at the intersection of commercial, technical, strategy, and operations, interacting with teams and executives inside and outside of OpenAI. About the Role We are seeking experienced Data Center Electrical Design Engineers with expertise in designing, operating, and maintaining large-scale data center campuses. The ideal candidate for this role will have extensive background and experience in design and managing critical equipment and facilities, design and operation of MEP (Mechanical, Electrical, Plumbing) systems, and overseeing operational activities from initial phases of Data Center build through delivery and ongoing maintenance. The ideal candidate will have a strong technical background, operational leadership experience, and a proven ability to collaborate with external vendors on critical infrastructure. This role offers the opportunity to lead transformative data center projects with high visibility and impact. If you are passionate about delivering cutting-edge infrastructure solutions, we encourage you to apply. Key Responsibilities Oversee building and MEP design, operation, and maintenance, including reviewing building and MEP drawings and proposals across all project phases. Lead operational activities for large-scale data center campuses, from early design phases through delivery and daily operation. Operate and maintain critical data center facilities and equipment, ensuring reliability and performance. Collaborate with external vendors to select, procure, and manage critical equipment, such as generators, UPS, chillers, and CDUs. Provide technical expertise on all aspects of data center building, equipment, and operational systems,

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE At Everpure, we are building the future of supply chain operations, and trusted master data is the foundational bedrock of our global scale. As our Supply Chain Master Data Management Data Steward, you will operationalize our master data governance framework by ensuring core enterprise data is accurately created, validated, and managed. Partnering closely with global Supply Chain, Order Management, IT, and external Contract Manufacturers, you will lead data lifecycle workflows to eliminate operational friction and ensure structural data health. Your dedication to data quality will directly safeguard downstream transaction reliability, empowering our entire business to execute flawlessly. WHAT YOU'LL DO Govern Master Data Lifecycles: Execute and own the end-to-end creation, maintenance, enrichment, and change control activities for critical supply chain domains (item, product, bill of materials, sourcing, and logistics) across global ERP systems (SAP). Enforce Data Quality & Validation: Active monitoring of master data movement across integrated platforms, owning exception handling, validation checks, and rapid remediation support to eliminate data sync failures and transaction delays. Streamline External Supply Ecosystems: Coordinate and align with external Contract Manufacturers to manage and validate shared critical data structures, ensuring flawless manufacturing and supply execution. Champion Process Stand

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. The Senior External Communications Manager leads the development and execution of strategic media relations and external communications initiatives that bolster the organization's reputation and market positioning. This role translates complex data and business insights into compelling narratives that resonate with media, analysts, partners, clients, and other key external audiences. This is a highly visible role that works closely with senior leaders across the organization to shape and amplify strategic communications priorities that support the business.

Data Engineer Particle41 is seeking a talented Data Engineer to join our team. You will design, build, and maintain data pipelines and infrastructure, support client-facing data visualization, and contribute to AI-assisted data workflows. You will work across the full data lifecycle — from raw ingestion to polished, decision-ready output — in collaboration with cross-functional teams. In This Role You Will Software Development Design, develop, and maintain scalable ETL/ELT pipelines to process large volumes of data from diverse sources. Build and optimize data storage solutions — data lakes and data warehouses — for efficient retrieval and processing. Integrate structured and unstructured data from internal and external systems into a unified view for analysis. Ensure data accuracy, consistency, and completeness through validation, cleansing, and transformation. Maintain clear documentation for data processes, tools, and systems. Data Visualization Build and maintain Tableau dashboards and reports that translate complex datasets into clear, decision-ready visuals. Design data models and extracts optimized for Tableau performance, including live connections and published data sources. Apply data visualization best practices — chart selection, layout, color, and interactivity — to produce client-ready output. Partner with stakeholders to understand reporting needs and translate them into visual solutions. Support ad hoc analysis using Tableau, Python-based charting (matplotlib, seaborn, plotly), or similar tools. AI and Data Support Support AI/ML workflows by building and maintaining the data pipelines that feed model training, inference, and evaluation. Assist with data preparation for LLM and machine learning projects,

About Syllo Syllo is on a mission to transform litigation. Our product is an AI-powered litigation workspace that enables lawyers and paralegals to safely harness the power of language models throughout the litigation life cycle. Since going to market, we have gained a diverse group of enterprise customers, including some of the biggest law firms in the country, and we are quickly expanding. By reducing the expense of litigation industry-wide, we aim to improve access to high-quality representation and promote the alignment of legal outcomes with merit. We’re looking for a Data Security Compliance Director who will own the compliance-side and business operations related to Company’s data security function. About the role Syllo is a legal technology company building infrastructure that law firms and legal teams trust with sensitive data. Compliance isn't a checkbox here, it's a product feature. We're looking for a Data Security Compliance Director to own our certification programs, manage vendor security relationships and processes, own the accurate and timely completion of our security disclosures in the sales context, and keep our posture audit-ready year-round. This role sits at the intersection of compliance and engineering. While this role does not own the security of our technical stack from an engineering perspective, you will work directly with technical teams to implement controls, close evidence gaps, and translate technical postures and requirements into concrete and well communicated action. Responsibilities - ISO 27001. Maintain and continuously improve our Information Security Management System. Manage internal audits, corrective actions, and annual surveillance cycles through Vanta. - SOC 2 Type II. Coordinate evidence collection, liaise with external auditors, and drive remediation across engineering and operations. - Vendor security. Lead vendor security assessments, manage VSQ responses (inbound and outbound), and maintain a tiered

HackerRank helps companies like NVIDIA, Amazon, and Microsoft hire and upskill the next generation of developers based on skills, not pedigree. Our platform is trusted by over 2,500 of the world’s most innovative companies to build strong engineering teams ready for what’s next. Software has entered an era where humans and AI build side by side. As this shift accelerates, the definition of strong technical talent is changing. We give companies better ways to identify and invest in next-generation skills. People at HackerRank care deeply about the impact of their work and sweat the small details so our customers can be wildly successful with products they genuinely love to use. We move with urgency and believe great outcomes come from high standards. About the role We are looking for a Senior AI Data Operations Manager to own and run our end-to-end LLM model data creation pipeline from sourcing and managing vendors, to coordinating with engineering teams to evaluate model performance to closing the loop by creating targeted data for edge cases ensuring the data our models train on meets the highest quality standards. This role will manage the end-to-end AI data pipeline across 10+ AI features spanning multiple products on our platform This is a cross-functional operations role that sits at the intersection of ML, product, and operations management. You will be the connective tissue between our machine learning engineers, internal annotators, and external vendors, translating technical requirements into actionable data creation workflows and ensuring every batch of data that reaches our models is accurate, well-annotated, and fit for purpose. Critically, you will also drive automation across the pipeline, designing and deploying AI agents that eliminate manual bottlenecks and make the entire operation smarter over time. What you will do Own the full AI feature development lifecycle, from sourcing data to quality management and relationship building at scale. Design an

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As one of our first Data Scientists dedicated to policy work, you will play a key role in ensuring Anthropic's work is understood by policymakers around the world. You'll sit at the intersection of data science and public affairs, transforming internal product usage and survey data into clear, accurate, and consistent evidence the Policy team can use to inform its positions, demonstrate Anthropic’s relevance to policymakers, and measure the impact of its work. Your analyses will directly inform how legislators, regulators, and the public understand Anthropic's footprint and contribution. This is a highly cross-functional role that is foundational to Anthropic's mission of bringing powerful AI to the world in a way that benefits humanity. Key responsibilities Partner with product and business teams across the company to produce supporting analyses and data collateral for specific policy position papers and partnership conversations Determine which metrics faithfully represent our company to legislators, regulators, and the public Own the dashboards and pipelines that keep externally-shared numbers consistent, so the Policy team can move quickly without creating discrepancies Use AI tools to aggregate news, policy developments, and other public data sources to track trends and provide a clear picture of the evolving regulatory landscape Develop measurement frameworks for policy communications, paid media, and public-affairs campaigns Design and implement policy analyses to support internal position development or measure the impact of policy implementation for external audiences Minimum qualifications Proficiency in Pytho