Product Data Management Engineer Jobs

We're looking for a Senior Engineer with a strong background in computer science fundamentals, systems design, experience in the Java ecosystem, streaming systems, and data-intensive applications to join our engineering team. In this role, you will be instrumental in designing, building, and optimizing the underlying data structures, algorithms, and database interactions that power our generative AI platform, code generation and migration tools. This involves crafting sophisticated orchestration layers, robust integration points, and high-performance data systems that seamlessly connect and leverage advanced AI capabilities for code generation and building a sophisticated data migration suite using a modern technology stack, which includes Java, Spring Boot, Kafka, Debezium, and React.You will work on critical components that ensure the scalability, efficiency, and reliability of our services, collaborating closely with AI researchers, product management and other engineers to design and implement cutting-edge products that solve complex customer challenges.. We are looking to speak to candidates who are based in Sydney for our hybrid working model. The ideal candidate for this role will have 6+ years of engineering experience in backend systems, distributed systems, or core platform development. Proficiency in one or several of Java, Rust, C/C++, and/or Python, with a strong understanding of systems-level programming, memory management, and performance tuning. Extensive experience with streaming data platforms such as Apache Kafka and Change Data Capture (CDC) tools like Debezium Extensive experience with relational data modeling and hands-on experience with at least one SQL database (Postgres, MySQL, etc) Exposure to client-side technologies such as JavaScript and React is a plus Good understanding of algorithms, data structures and their time and space complexity Curiosity, a positive attitude, and a drive to continue learning Excellent verbal and wri

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. The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. Agentic AI is at the center of how we scale that mission. We fine-tune and align open-source models, build AI-powered support agents, and develop end-to-end AI agents for safety case management, systems that reason over complex, high-stakes cases and drive them to resolution. SCC brings together ML, data, backend, and product engineers alongside data scientists and operations partners to transform these systems. As a Machine Learning Engineer on the SCC team, you will fine-tune and align models and build AI Agents that power how riders and drivers get help. Your work spans the full loop: post-training open-source models for our domain, composing them into multi-step agents, and building the evaluation that proves they are safe to ship in a customer-facing, safety-critical setting. Post-train and adapt open-source LLMs for SCC use cases using SFT, LoRA, and preference-tuning methods (RLHF, RLAIF, RLVR). Design and build AI-powered support agents and end-to-end agents for safety case management using LangGraph or equivalent agentic frameworks. Own the evaluation data flywheel, offline and online, that defines what "good" looks like and build benchmarks for the team to hill-climb. Turn interaction feedback into training data and learning signals, closing the data flywheel that continuously improves the models. Responsibilities: Conduct literature review and build post-training fra

MongoDB is growing its team in Sydney, focusing on building intelligent tools that help customers understand and modernise their application codebases. The Application Modernisation Platform (AMP) guides customers through the entire journey of modernising their applications — from legacy relational platforms to modern, scalable systems built on MongoDB. The App Analysis & Modelling team owns the critical first stage of this journey: building the context that powers everything downstream. The team builds code analysis tools that construct code dependency graphs and generate deep insights for codebases, giving customers a clear understanding of their existing applications before transformation begins. The team also designs schema recommendation engines that analyse signals such as existing relational schemas and query patterns to inform data modelling decisions. Our work sits at the intersection of analysis, data modelling, and AI — helping developers make confident, data-driven decisions as they transition to MongoDB. We are looking for a Senior Software Engineer who is passionate about building scalable backend systems and applications. As we expand our use of AI to power smarter analysis and recommendations, the ideal candidate will bring strong backend engineering fundamentals with the ability to contribute across the full stack. You will collaborate closely with product management and other engineering teams to design and deliver cutting-edge features that guide customers through complex modernisation journeys. We are looking to speak to candidates who are based in Sydney for our hybrid working model. The ideal candidate will have 5+ years of commercial software development experience with strong proficiency in Python and/or Java Extensive Experience designing and building scalable, high-performance APIs and backend services Solid understanding of relational data modelling and SQL (Oracle, PostgreSQL, MySQL, or similar), including schema design and query opti

MongoDB is growing its team in Sydney, focusing on building intelligent tools that help customers understand and modernise their application codebases. The Application Modernisation Platform (AMP) guides customers through the entire journey of modernising their applications — from legacy relational platforms to modern, scalable systems built on MongoDB. The App Analysis & Modelling team owns the critical first stage of this journey: building the context that powers everything downstream. The team builds code analysis tools that construct code dependency graphs and generate deep insights for codebases, giving customers a clear understanding of their existing applications before transformation begins. The team also designs schema recommendation engines that analyse signals such as existing relational schemas and query patterns to inform data modelling decisions. Our work sits at the intersection of analysis, data modelling, and AI — helping developers make confident, data-driven decisions as they transition to MongoDB. We are looking for a Software Engineer who is passionate about building scalable backend systems and applications. As we expand our use of AI to power smarter analysis and recommendations, the ideal candidate will bring strong backend engineering fundamentals with the ability to contribute across the full stack. You will collaborate closely with product management and other engineering teams to design and deliver cutting-edge features that guide customers through complex modernisation journeys. We are looking to speak to candidates who are based in Sydney for our hybrid working model. The Ideal Candidate Will Have 3+ years of commercial software development experience with strong proficiency in Python and/or Java Experience designing and building scalable, high-performance APIs and backend services Solid understanding of relational data modelling and SQL (Oracle, PostgreSQL, MySQL, or similar), including schema design and query optimisation Good und

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 are looking for an experienced Mechanical Engineer with 7+ years of experience in design of IT hardware from chip/package to system levels. You’ll work alongside experts in thermal, mechanical, electrical, software, and systems engineering to support the design, analysis, and validation of mechanical and thermal systems that ensure the reliability, efficiency, and longevity of mission-critical hardware. This position requires strong analytical skills, hands-on testing experience, and the ability to work in a fast-paced, cross-disciplinary environment. 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: Lead mechanical design for AI supercomputer product in the data center application Collaborate with the cross functional team to design and optimize thermal solutions for data center hardware, including chips, power modules, and system-level cooling architectures Collaborate with cross-functional teams to integrate thermal management strategies into hardware design, from concept to mass production Design and validate mechanical systems, including chassis, enclosures, cooling systems, and high-power connections, ensuring alignment with performance and reliability standards. Perform 3D modeling, FEA, tolerance analysis, and prototyping, ensuring manufacturability and a

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Technical Program Management Team The Engineering Technical Program Management Team’s mission is to enable Okta to deliver on key strategic goals by bringing groups together across Engineering, Security, Legal, Compliance, Product Management, and Customer Support. Engineering TPMs drive prioritization, planning, execution, and ensure transparency while managing success criteria. The Principal Technical Program Manager, Engineering Opportunity As a Principal Technical Program Manager in the Engineering TPM Team, you will partner with various groups across Okta to build and deliver key Engineering initiatives. You will be the point person for clarifying strategic level goals and outlining the execution plans to achieve them. You will work within and across teams to prioritize and execute on key objectives. Employing both a strategic and tactical approach is a requirement in this role. You will not only have strong TPM experience, but also experience implementing complex efforts within Engineering or Infrastructure in a SaaS and agile environment. *This position requires the ability to access Impact Level 4 & 5 (IL4 and IL5) data, as defined by the Department of Defense (DoD) Cloud Computing Security Requirements Guide. As a condition of employment for this position, the successful candidate must be able to submit documentation establishing U.S. Person status (e.g. a U.S. Citizen, National, Lawful Permane

About the Role We are seeking an experienced Privacy Lead to establish, manage, and continuously enhance the organization's Privacy Program across business functions, products, technology platforms, and third-party ecosystems. The ideal candidate will possess deep expertise in privacy regulations including India's Digital Personal Data Protection Act (DPDP Act), GDPR, and privacy governance frameworks. The individual will partner closely with Legal, Compliance, Information Security, Product, Engineering, Risk, HR, and Business teams to ensure privacy-by-design principles are embedded into organizational processes and technology solutions. The Privacy Lead will serve as the subject matter expert for privacy governance, regulatory compliance, privacy risk management, data subject rights management, privacy impact assessments, and data protection controls. Key Responsibilities Privacy Governance & Strategy -Develop and execute the enterprise-wide Privacy Program and Privacy Governance Framework. -Define privacy policies, standards, procedures, and controls aligned with regulatory requirements. -Establish Privacy-by-Design and Privacy-by-Default principles across products and services. -Build privacy risk management and privacy control monitoring mechanisms. -Advise executive leadership on emerging privacy risks and regulatory developments. -Act as the organization's privacy subject matter expert for audits, inspections, and regulatory reviews. Regulatory Compliance Lead compliance initiatives for: -Digital Personal Data Protection Act (DPDP Act), India -GDPR (General Data Protection Regulation) -ISO 27701 Privacy Information Management System -RBI data governance and customer data protection requirements -Applicable privacy and data protection obligations relevant to the Banking, FinTech, Payments, and Technology sectors Responsibilities include: -Regulatory gap assessments -Compliance monitoring -Privacy control implementation -Privacy risk assessmen

About the Team OpenAI’s Education team is building products that advance how people learn with AI. The team works across higher education institutions, K-12 districts, and country-level partnerships, including applied research on how AI affects learning and cognitive outcomes. The team owns owns ChatGPT Edu, ChatGPT for Teachers, and related product/research work. The team partners closely with go-to-market, research, Consumer Learning, and model teams to turn education-specific insights into product experiences that can improve ChatGPT more broadly. Some of our recent work: New Education Plugins for ChatGPT Work and Codex New tools for understanding AI and learning outcomes Education for countries Advancements in higher education Early product work - Introducing Study Mode About the Role We’re looking for a hands-on Tech Lead Manager to lead and manage a team of senior full-stack engineers building AI-native learning experiences in ChatGPT. This person will combine technical execution, product judgment, and people leadership: they will write and ship code, manage engineers, and help shape the product direction for how students and Educators use AI. In This Role, You Will Lead and manage a team of three senior full-stack engineers. Build product experiences for ChatGPT Education, ChatGPT for Teachers, and AI-native learning workflows. Partner with research teams on field studies, randomized control trials, classifiers, data pipelines, and cognitive-outcome measurement. Collaborate with Consumer Learning and model teams to translate education insights into broader ChatGPT behavior and product improvements. Drive execution across product, engineering, research, go-to-market, and partner teams. Help define product strategy, priorities, and delivery plans for a new product pod. You Might Thrive In This Role If You Have several years of direct people-management experience with engineers. Are still highly technical and comfortable doing IC engineering work. Have strong pr

Position Overview: A Junior Research Analyst within the Diligent Market Intelligence function supports subject matter expertise in specialized research areas such as compensation, governance, activism, voting, and risk. Their main responsibilities include assisting in the design and management of data collection methodologies, overseeing third-party service provider workflows, and ensuring high-quality, timely data delivery. They are also expected to execute manual data collection from global sources, maintain strong quality assurance practices, and collaborate closely with Product and Engineering teams to ensure operational efficiency and accuracy. Additionally, Junior Research Analysts take ownership of specific daily and weekly tasks, contribute to ongoing projects, and play a key role in training service providers while keeping process documentation clear and up to date. The role requires strong numeracy, attention to detail, independent work habits, and a proactive approach to continuously improving research products and processes. Key Responsibilities: Proactive communication and management of outsourcer workload. Conduct data collection tasks to uphold the integrity of our database and keep it current. Execute systematic checks to identify data inaccuracies and operational inefficiencies as per predefined protocols. Provide regular updates and reports to the Vertical lead on progress and challenges. Take ownership of specific daily and weekly tasks, as well as ongoing projects within the assigned research vertically. Required Experience/Skills: Entry level Analytical approach and problem-solving attitude Strong written and verbal communication skills Ability to manage deadlines Ability to adapt to difficult workload demands, e.g., time/resource constraints Proficiency in Microsoft Office, especially Excel About Us Diligent is the AI leader in governance, risk and compliance (GRC) SaaS solutions, helping more than 1 million users and 70

Roles & Responsibilities Displays structured problem solving, application of right tools & techniques to solve open ended problems, Creates productized analytics solutions or frameworks independently. Understand Business & product problems and come up with deep data backed solutions. Root cause analysis and Deep dive analysis of certain product problems Running and maintaining the reporting system, presenting insights at a weekly forum Building templates, dashboards in Power BI, Gsheets for operational and management reporting Data extraction as per business request for Ad hoc analysis Business analysis and understanding Evaluating metrics to be tracked as per business goals, exploring other available metrics for deeper understanding of product performance Work in a fast-moving environment, across multiple projects with varying levels of complexity and detailing Desired Skills and Experience: 3 - 5 years working with large data sets and conducting quantitative analysis Some understanding of Statistics and prior experience of building statistical models (e.g. hypothesis testing, product experimentation, A/B Testing, regressions). Excellent knowledge SQL and intermediate knowledge of data manipulation language such as R/Python Previous experience with working on ecommerce funnels, retention Ability to think through product and business metrics to assess product features Knowledge of business modelling and basic knowledge of financial metrics, would be a bonus Quick learner and ability to work in dynamic work environment Team player and comfortable interacting with people from multiple disciplines Established expertise in designing new dashboards, identifying the right metrics, layout; displays proficiency in building dashboards on Power BI using best practices and intuitive Qualifications Bachelor’s in engineering, Computer Science, Economics, Statistics, or related discipline from a reputed institute ...........................

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? As a Member of Technical Staff in the Safety for Agents team, you will make a meaningful impact on the development of better, fairer, more trustworthy, and more secure Large Language Models (LLMs). Your primary focus will be on data generation, post-training algorithms, and evaluation methods to ensure Safety in the next generation of models that can access external resources and take actions in the world. You will work closely with other cross-functional machine learning teams and data annotation teams, and will also collaborate with product and policy teams. This role combines expertise in machine learning, ethical and responsible AI, experimental design, and data generation and management. It will require curiosity to tackle totally new scientific problems, engineering skills to implement the pieces we need to test solutions to these, and a desire to dive into messy data and results. You will be on a small team with a lot of autonomy and decision-making power, responsible for making the next generation of LLMs better for society as a whole. Please Note: The existing team work in offices in London, Edinburgh, Pa

About Zinnov Zinnov is a global management consulting firm that helps organizations make decisions that actually get used — and deliver results that matter. For over two decades, we’ve partnered with leading enterprises, high-growth technology companies, and investors to answer some of the toughest questions they face: Where should we invest? How do we scale globally? What capabilities will win in the next decade? Our work shapes market entry strategies, global operating models, M&A decisions, and long-term growth bets. We’re known for being data-led, execution-focused, and outcome-driven — not opinion-heavy slideware. At Zinnov, how you work matters as much as what you deliver. We value independent thinking, crisp communication, and early ownership. With 450+ professionals across 10 global offices, we work across industries including Digital Services, ER&D, Enterprise Software, Semiconductors, Healthcare, BFSI, Automotive, Media & Telecom, and Private Equity. Zinnov isn’t for everyone. It’s for people who want steep learning curves, honest feedback, and the chance to see their work influence real business decisions — not just presentations. About the Role As a Senior Data Engineer , you will own the data foundation of Zinnov’s GCC Intelligence Platform—building reliable multi-tenant pipelines and KPI-ready datasets across Finance and Hiring domains. Your work enables downstream dashboards and AI agents to operate on clean, reconciled, governed data. What You’ll Do Data Pipelines & Medallion Architecture Build andmaintainingestion pipelines from source systems (e.g., Dynamics, Workday, Airtable, SFTP feeds). Design and implement Medallion pipelines (Bronze → Silver → Gold) across Finance and Hiring data. Build reconciliation and gating logic to ensure only validated data reaches Gold. Multi-tenant Data Modeling Design multi-tenant PostgreSQL schemas with row-level s

As a Staff Product Manager on Datadog's Observability Data Platform (ODP) , you will lead product management for a portfolio of foundational platform bets — work that changes the cost structure and capability of the platform itself, not the cost of any single feature. Among ODP’s portfolio of engineering work are efforts to bring the platform's unit cost down meaningfully each quarter, plus a slate of architectural bets aimed at order-of-magnitude cost reduction over the longer horizon. The work you'll lead reshapes how Datadog ingests, routes, and exposes telemetry value to customers — and is foundational to how every product team in Datadog's ecosystem will think about telemetry economics going forward. This role reports to the Group Product Manager of ODP. What You'll Do: Set product direction across foundational platform bets by defining problems and desired outcomes, partnering with engineering to determine slices of work that drive value in phases for users and the business. Collaborate on the long-term cost-and-value architecture of the platform — how value-aware telemetry, innovative data engines, and customer-facing cost stories fit together over multiple quarters. Develop and defend sizing and impact estimates for large, diffuse programs — credibly produce the analysis that engineering leadership and pricing partners need to make resourcing and prioritization calls. Anticipate and communicate market trends in telemetry economics and agentic observability and how they shape platform investment. Develop deep understanding of cost-to-serve by partnering with engineering on the unit economics of the data platform and bring that cost-profile understanding into collaborative discussions with product verticals about customer-facing trade-offs. Surface the customer-positive angles in cost work that engineering-led optimization tickets don't currently make visible. Deliver concise written and verbal communication to executive, engineering, and customer audien

The Product Management team drives Asana’s product strategy and execution, translating customer needs and opportunities into a compelling roadmap and working cross-functionally to deliver impactful solutions for team productivity and collaboration. We're defining a new category of technology as the human agent operating system by inventing new ways for teams to work together more efficiently. Our team works directly with Engineering, Design, Experience Research, and Data Science, as well as with Sales, Support, and Marketing to ship great products. You’ll take part in every type of product work here, from strategy to product to process improvements, by conceptualizing, launching, and iterating on Asana itself for millions of teams around the world. We are looking for an experienced Product Manager to join our Enterprise Data Governance team. Our team owns the strategic platform capabilities that govern the full lifecycle of customer data, including retention, migration, auditing, export, and operational governance. We are foundational to Asana's enterprise success, providing the controls and policy frameworks that allow large organizations to meet complex regulatory requirements and securely adopt AI. As a Product Manager here, you will bridge the gap between technical infrastructure and enterprise customer needs, partnering closely with Engineering, Security, Legal, and Design to reduce operational burden and build the governance foundation that helps people and AI agents collaborate safely at scale. This is a high-impact role at the intersection of enterprise trust, regulatory compliance, and platform strategy, directly driving Asana’s growth in highly regulated industries. This role is based in our Vancouver office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams wit

About the Team Our team turns OpenAI’s latest model capabilities into polished, trusted products for consumers and developers. We build the end-to-end experiences including product surfaces, platform layers, and developer workflows that make cutting-edge AI accessible, useful, and dependable at scale. OpenAI’s Financial Engineering (FinEng) team powers how revenue flows through our products - pricing and packaging, checkout, payments, subscriptions, and the financial infrastructure behind them. We partner closely with Engineering, Data Science, Risk, Finance, and Go-to-Market to make paying for OpenAI products seamless, reliable, and efficient worldwide. We pair rapid innovation with a rigorous approach to responsible deployment. Safety and trust are built into how we design, ship, and learn from real-world usage, so these tools deliver meaningful value while aligning with OpenAI’s mission. About the Role We are seeking an experienced Product Manager to scale the product efforts and technical strategy within our Financial Engineering team. The ideal candidate has prior experience in billing, finance, and accounting, ideally also building solutions for commercial users of varying sizes from small scale to enterprise. This role requires close collaboration with our product, finance, operations, and engineering teams. This position is based in San Francisco, CA. We utilize a hybrid work model with 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Develop a strategy and roadmap to efficiently scale the billing operations and customer experience behind OpenAI’s growing product portfolio Identify and execute opportunities to improve the order-to-cash processing for OpenAI’s largest and most strategic customers Build AI powered tooling for key partner teams such as Finance and User Operations to drive better decisions and business outcomes Collaborate with other product teams to defining OpenAI’s evolving monetization s