Knowledge And Data Architect Jobs

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with

Opportunity Overview: We are seeking a Lead Data Engineer to drive the design and delivery of our cloud-native healthcare data platform. You will lead the implementation of scalable data solutions built on AWS, Apache Iceberg, Lake Formation, Glue Catalog, Athena, dbt, and modern orchestration frameworks. This role combines deep hands-on engineering with technical leadership and collaboration across platform, analytics, and business teams. What you’ll do: Lead Data Engineering Initiatives Lead delivery of complex data engineering projects across multiple teams Drive technical execution from design through production deployment Establish scalable implementation patterns Build and Optimize Data Platforms Design and implement batch and near-real-time pipelines Build reusable ingestion, transformation, validation, and publishing frameworks Support modernization of legacy workloads Lakehouse Engineering Lead Apache Iceberg implementation and optimization Define standards for schema evolution, partitioning, compaction, and metadata management Ensure efficient storage and query performance Data Quality and Reliability Implement data quality frameworks Drive observability and monitoring practices Improve operational excellence and reliability Technical Leadership Review architecture and design proposals Conduct code reviews and engineering reviews Mentor engineers and establish best practices ISMS roles and responsibilities: Good knowledge of Information practices. Assist the manager in all the information security activities implementation and maintenance process. Ensuring the team and imparted with Competence related to Information security Responsible for implementation of security policies and procedures and report any issues to the Information Security Manager. Required Qualifications: 8–12 years of Data Engineering experience. Experience leading enterprise-scale data initia

About Dot Collective We are a new generation consultancy based across UK and EU and founded on the premises of the engineering excellence and empowering people to make an impact. We work with all modern tech stacks and typically run agile scrum on all our projects. About you Are you passionate about data and its transformational powers? Do you like being able to make a huge difference in a limited period of time? We might be just the right place for you. Your key skills and capabilities: Strong SQL and Python skills Data modelling experience (dimensional, relational, or similar) Experience building and maintaining backend systems Familiarity with Microsoft Azure Understanding of APIs, containers, and backend development best practices Implementing cloud-native data platforms Engineering scalable and reliable pipelines Good knowledge of distributed computing with Spark Understanding of cloud architecture principles and best practices Hands-on experience in designing, deploying, and managing cloud resources Agile ways of working Experience in cloud automation and orchestration using tools such as CloudFormation or Terraform Monitoring and performance tuning of cloud-based applications and services Nice to haves: Experience with Snowflake, dbt, CubeJS Experience with Databricks, PySpark, ML workflows Experience with containerized deployments (Docker, Kubernetes, Azure Container Apps). Frontend development experience (React, Next.js, TypeScript) Infrastructure-as-code (Terraform, CloudFormation) Model Deployment & Serving – Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance Monitoring & Retraining – Set up model drift detection, performance monitoring, and automated retraining ML Pipelines & CI/

About Dot Collective We are a new generation consultancy based across UK and EU and founded on the premises of the engineering excellence and empowering people to make an impact. We work with all modern tech stacks and typically run agile scrum on all our projects. About you Are you passionate about data and its transformational powers? Do you like being able to make a huge difference in a limited period of time? We might be just the right place for you. Your key skills and capabilities: · Implementing cloud-native data platforms · Engineering scalable and reliable pipelines · Good knowledge of distributed computing with Spark · Understanding of cloud architecture principles and best practices · Hands-on experience in designing, deploying, and managing cloud resources · Excellent python and SQL skills · Agile ways of working · Experience in cloud automation and orchestration using tools such as CloudFormation or Terraform · Monitoring and performance tuning of cloud-based applications and services Nice to haves: (MLOps): Model Deployment & Serving – Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance. Monitoring & Retraining – Set up model drift detection, performance monitoring, and automated retraining ML Pipelines & CI/CD – Automate end-to-end ML workflows We expect you to have some knowledge about how to architect, design, develop, deploy, and operate a data platform. Our promise to you We will always see you as a human being and will do our very best to support your needs and wellbeing – well-designed co-working and collaboration spaces, remote working patterns that work for you, parenting leave, sabbaticals

About Dot Collective We are a new generation consultancy based across UK and EU and founded on the premises of the engineering excellence and empowering people to make an impact. We work with all modern tech stacks and typically run agile scrum on all our projects. About you Are you passionate about data and its transformational powers? Do you like being able to make a huge difference in a limited period of time? We might be just the right place for you. Your key skills and capabilities: · Implementing cloud-native data platforms · Engineering scalable and reliable pipelines · Good knowledge of distributed computing with Spark · Understanding of cloud architecture principles and best practices · Hands-on experience in designing, deploying, and managing cloud resources · Excellent python and SQL skills · Agile ways of working · Experience in cloud automation and orchestration using tools such as CloudFormation or Terraform · Monitoring and performance tuning of cloud-based applications and services Nice to haves: (MLOps): Model Deployment & Serving – Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance. Monitoring & Retraining – Set up model drift detection, performance monitoring, and automated retraining ML Pipelines & CI/CD – Automate end-to-end ML workflows We expect you to have some knowledge about how to architect, design, develop, deploy, and operate a data platform. Our promise to you We will always see you as a human being and will do our very best to support your needs and wellbeing – well-designed co-working and collaboration spaces, remote working patterns that work for you, parenting leave, sabbatical

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We're looking for a Lead Data Engineer to join our Data Engineering & Architecture team. In this role, you'll help grow a Data Platform that makes it easier for teams across our company to work with data confidently and effectively . Your work will directly support our business goals not just by keeping data flowing, but by turning it into something people can actually use and trust. This is a great opportunity for someone who enjoys both the technical craft of data engineering and the human side of it: collaborating with partners, sharing knowledge, and helping others get more out of the tools and systems you build together . What You Will Be Doing You'll design, maintain, and improve the pipelines and infrastructure that power our data platform. Day to day, that means working across the full data lifecycle — from ingestion and streaming to transformation and delivery — using tools like Apache Airflow, Spark, Iceberg, Kafka, Flink, and dbt Labs. Beyond the technical work, you'll spend meaningful time with stakeholders to understand what they need and help define how data should flow across systems. That includes co-creating data contracts, writing clear documentation, and guiding teammates on how to get the most out of the platform. A few other things you'll take on: Moni

The Data Engineering team is responsible for building ETL pipelines that populate the Internal Data Platform, which drives analytics that help the company run more efficiently. Our team builds highly performant and scalable processes that extract massive datasets and makes those datasets available for querying in an optimal way. We are looking to speak to candidates who are based in Gurgaon for our hybrid working model. What you’ll do Guide the Data Engineering team on building highly performance ETL pipelines using Spark and other Big Data technologies Help design the architecture of our Internal Data Platform to support the implementation of a robust medallion architecture Provide thought leadership on ways to achieve infrastructure cost savings on Cloud hyperscalers Design and build AI agents that can help automate many of the common development and support tasks that the team performs Work with Security and Compliance teams to ensure that datasets have appropriate permissions and regulations in place Work with our Data Platform, and Governance sibling teams to make data scalable, consumable, and discoverable We’re looking for someone with 10+ years experience working on enterprise data lakes/warehouses 5+ years of Spark and Python experience 5+ years of direct hands-on experience working with AWS or GCP Thorough AI knowledge, particularly with codegen tools and agentic frameworks Hive, Iceberg, Glue, or other technologies that expose big data as tables Familiarity with different big data file types such as Parquet, Avro, and JSON Exposure to real-time or streaming data technologies is a plus Success Measures In 3 months, you'll have a thorough understanding of the architecture of MongoDB’s internal Data and AI ecosystem In 6 months, you'll have owned the delivery of a large project from start (scoping, design) to finish (delivery) In 12 months, you'll have designed new features, led development work, and become a go-to expert on parts of the system About MongoDB

About the Team The Merchant Knowledge Platform team, part of DoorDash’s Merchant organization, builds the systems that serve merchant, store, menu, and catalog data to experiences across DoorDash, Wolt, and Deliveroo. Our platform connects merchant information to the experiences people rely on every day, from discovering stores and searching for products to placing orders. We’re building the next generation of this global platform to support growing data volumes, new product capabilities, and AI-powered experiences. Our team brings together experienced technical leads and engineers early in their careers, with a shared commitment to engineering excellence and learning. About the Role We’re looking for an Engineering Manager to lead a team of talented engineers building and operating a platform at the core of our global marketplace. You’ll own the team’s technical direction and roadmap, working closely with engineers on architecture and design decisions while supporting their growth. You’ll partner with teams across the company to understand their needs, set priorities, and build shared capabilities that make merchant data reliable and efficient to access at scale. You must be located in the New York Metro Area for this hybrid position. You’re excited about this opportunity because you will… Shape the technical vision and roadmap for a global merchant data platform that supports consumer and merchant experiences across three companies. Guide the design of distributed systems that serve large volumes of data with high availability, low latency, and consistent performance. Partner with engineering, product, and business teams to turn shared needs into reusable platform capabilities and make clear decisions about priorities and tradeoffs. Support, coach, and develop a team of engineers with a range of experience, helping them grow their technical skills and ownership. Improve platform reliability and engineering practices while helping the team use AI tools to lea

Role Overview Build the software services that power products, platforms, and better business decisions. As a Software Engineer II, you’ll develop scalable backend applications, APIs, integrations, and AI-enabled features using Python and cloud technologies. You’ll contribute to solutions from design through production, helping improve reliability, performance, security, and developer productivity. This is an opportunity to solve meaningful engineering challenges, grow your technical ownership, and collaborate with experienced engineers across the development lifecycle. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Design and build scalable backend services, REST APIs, integrations, and reusable software components using Python and, where relevant TypeScript. Develop data ingestion, transformation, service-to-service communication, and automation capabilities that support reliable product experiences. Contribute to AI-enabled features and use AI development tools responsibly to improve coding, testing, research, documentation, and delivery. Apply sound engineering practices across architecture, performance, security, testing, debugging, and maintainability. Deploy and operate services using AWS and CI/CD workflows, contributing to monitoring, troubleshooting, documentation, and continuous improvement. Partner with engineers and cross-functional colleagues through design discussions, code reviews, technical problem-solving, and knowledge sharing. These are the essentials you’ll need to get an interview 3–5 years of professional experience building and delivering production software in an agile environment. Strong hands-on experience with Python and backend development, including APIs, integrations, or service-oriented applications. Experience working with cloud platforms, preferably AWS, and familiarity with deployment or CI/CD practices. Working knowledge of software design principles, testing, debugging, performance optimization, an

Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the team The Finance Data Team is responsible for the data infrastructure that powers OKX's compliance, regulatory, and financial reporting operations globally. Our Finance Data domain covers everything from raw transaction ingestion to consolidated group financials — supporting statutory reporting, board-level financials, and audit readiness across 100+ markets. This is a team that treats data correctness as a non-negotiable. We operate at the intersection of engineering rigour, financial domain knowledge, and regulatory accountability. About the role We are looking for a Staff Data Engineer to be the technical anchor for Finance Data at OKX. You will define how Finance data is architected, validated, and delivered, and set the standard for how the team operates in an AI-native way. You will work directly with Finance, Accounting, and Treasury stakeholders to ensure that financial data is complete, reconciled, traceable, and audit-ready. You will also be the domain's primary escalation point and the technical voice of Finance Data within the broader engineering organisation

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 We're looking for a research engineer who believes that visual and spatial reasoning are core to fully unlocking the capabilities of LLMs. On the Vision team, you'll own the end-to-end process of creating training data and RL environments targeting visual knowledge work: identifying long-horizon and vision-heavy tasks, building evals, designing rewards, and scaling data. This is a unique role that combines applied research with hands-on data work. It's also highly collaborative — you'll partner with external vendors, pretraining, RL, and product teams to make sure the environments you build translate into real-world knowledge work capabilities. What you'll do: Own the data strategy for vision capabilities end-to-end, from building evals and scaling RL environments Manage technical relationships with external data vendors, including writing task specifications, evaluating visual data and annotation quality, and iterating on reward design Develop and improve QA frameworks that catch reward hacking and ensure environment quality at scale Run generalization experiments to measure how data strategy changes improve multimodal capabilities on held-out evaluations Partner with pretraining, RL, and product teams, and do the science that shows we’re all rowing in the same direction You may be a good fit if you: Have 7+ years of ML, computer vision, and software engineering experience through industry, academia, or other projects Have experience with reinforcement learning, reward design, or training data curation for large language or vision-language models Are familiar with the architecture, training, and operation of large visi

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: We are seeking a strategic and technically fluent Lead, IT Audit to join our Finance team reporting to the Head of Internal Audit. This is a broad, high-impact role spanning both IT SOX compliance and operational IT audits. You will help establish and elevate our technology controls program end to end — owning the IT SOX lifecycle, designing the IT general and application controls framework, embedding AI and automation into how we test and monitor controls, and delivering value-added operational IT and cybersecurity audits that strengthen how the company builds and runs its systems. You will partner with leaders across Engineering, Security, IT, Finance, and the business to ensure sound technology controls are built into how the company operates as we scale. This role is ideal for someone who thinks like a builder, not just an auditor — someone who can translate complex control and security requirements into practical, scalable processes in a fast-moving SaaS environment with modern cloud architecture and complex data flows. This role can be based in either San Francisco or New York City. We work from our offices on M

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Team: Our Business Development team is at the forefront of the AI ecosystem. We build strategic partnerships with the world’s leading Data and AI platforms, as well as ERP, CRM, and industry-specific vendors. We don’t just extend the Celonis platform; we embed our intelligence layer into the partner stack to power AI-driven transformation, growing ARR and scaling agentic deployments globally. The Role: You will own the end-to-end partnership lifecycle for our most strategic Data partners. Your mission is to position Celonis as the essential "context layer" for Enterprise AI. You will identify high-impact AI use cases, design joint Agentic solutions, and manage OEM accounts to ensure Celonis is the engine behind their intelligent automation. You will serve as the connective tissue between our partners and the Celonis Applied AI, Engineering, and Product teams. The work you'll do: Architect the AI Ecosystem: Demonstrate how the Process Intelligence Graph provides the context for a partner’s AI and LLM applications. Drive AI-First Sales Cycles: Support leadership in driving complex, multi-stakeholder sales cycles with tier-one software vendors (e.g., Coupa, Workday Salesforce, Veeva, Guidewire). Enable Agentic Workflows: Serve as t

About Pinecone Pinecone is the trusted AI knowledge company. Its trusted AI knowledge platform—including its Database, Nexus, and Marketplace products—power accurate, fast, and cost-effective AI applications for more than 10,000 customers and 1M developers worldwide. Pinecone's mission is to make AI knowledgeable. For more information, visit pinecone.io . About the Team and Role: We are hiring a senior/staff software engineer to help design and build core components of our next-generation knowledge retrieval system built for the AI era – search and retrieval infrastructure that powers high-quality, scalable, and enterprise-grade agentic systems. You’ll build the framework that allows our customers to connect knowledge–synthesized from structured and unstructured data–to modern LLM-powered applications, leveraging the world’s best-in-class vector DB supporting semantic search and hybrid retrieval. This role is ideal for someone who loves backend system architecture, distributed systems, and applied AI infrastructure. It is a high impact role with significant ownership across architecture, performance, and system reliability. Responsibilities: Design and build scalable platform components leveraging advanced retrieval via query planning, semantic and hybrid search, metadata-aware search, and LLM generation Design and build optimized indexing pipelines for structured and unstructured data Build backend services for semantic and hybrid retrieval, knowledge graph construction, and retrieval orchestration Improve retrieval quality through evaluation and observability frameworks Design APIs for internal and external user and agentic consumers Optimize latency, throughput and cost across large-scale inference and retrieval workloads Drive technical direction for reliability and security What You’ll Bring to the Table: To thrive in this role, you don't need to check every single box, but you should be deeply passionate about how to turn data into knowledge. Systems Expertise

About Pinecone Pinecone is the trusted AI knowledge company. Its trusted AI knowledge platform—including its Database, Nexus, and Marketplace products—power accurate, fast, and cost-effective AI applications for more than 10,000 customers and 1M developers worldwide. Pinecone's mission is to make AI knowledgeable. For more information, visit pinecone.io . About the Team and Role: We are hiring a senior/staff software engineer to help design and build core components of our next-generation knowledge retrieval system built for the AI era – search and retrieval infrastructure that powers high-quality, scalable, and enterprise-grade agentic systems. You’ll build the framework that allows our customers to connect knowledge–synthesized from structured and unstructured data–to modern LLM-powered applications, leveraging the world’s best-in-class vector DB supporting semantic search and hybrid retrieval. This role is ideal for someone who loves backend system architecture, distributed systems, and applied AI infrastructure. It is a high impact role with significant ownership across architecture, performance, and system reliability. Responsibilities: Design and build scalable platform components leveraging advanced retrieval via query planning, semantic and hybrid search, metadata-aware search, and LLM generation Design and build optimized indexing pipelines for structured and unstructured data Build backend services for semantic and hybrid retrieval, knowledge graph construction, and retrieval orchestration Improve retrieval quality through evaluation and observability frameworks Design APIs for internal and external user and agentic consumers Optimize latency, throughput and cost across large-scale inference and retrieval workloads Drive technical direction for reliability and security What You’ll Bring to the Table: To thrive in this role, you don't need to check every single box, but you should be deeply passionate about how to turn data into knowledge. Systems Expertise