Knowledge And Data Architect Jobs

Omada Health is on a mission to bend the curve of chronic disease. Job overview: We are dedicated to leveraging data to drive strategic decision-making and operational efficiency. Our team is passionate about harnessing the power of data to solve complex problems and deliver impactful insights. We are seeking a highly skilled and motivated Data Engineer to join our team. The ideal candidate will be responsible for designing, building, and maintaining robust data architectures and engineering data models and pipelines. This role will play a critical part in ensuring the integrity, scalability, and performance of our data processing and products. Key Responsibilities: Data Architecture: Design, develop, and implement scalable, secure, and efficient data solutions that meet the needs of the organization. Data Modeling: Create and maintain logical and physical data models to support business intelligence, analytics, and reporting requirements. Pipeline Engineering: Design, build, and optimize ETL (Extract, Transform, Load) processes and data pipelines to ensure smooth and efficient data flow from various sources. Data Integration: Integrate diverse data sources, including APIs, databases, and third-party data, into a unified data platform. Performance Optimization: Monitor and optimize the performance of data systems and pipelines to ensure low latency and high throughput. Data Quality and Governance: Implement data quality checks, validation processes, and governance frameworks to ensure the accuracy and reliability of data. Collaboration: Partner closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet their needs. Documentation: Maintain comprehensive documentation of data architectures, models, and pipelines for ongoing maintenance and knowledge sharing. Training: You'll train and collaborate with teammates effectively in data engineering best practices Technical Influence/Leadership: Recommends p

This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Senior Data Engineer - Payments At Adyen, we treat data and data artifacts as first-class citizens. In this role, you'll be at the core of our data strategy by helping us in building the best-in-class data platform for payments, and creating meaningful data products that drive our external and internal stakeholders. You'll also work in creating and maintaining robust reporting solutions that provide concise, reliable, and trustworthy intelligence to our customers. What you’ll do Collaborative Solution Development : Engage with a diverse range of stakeholders, including data scientists, analysts, software engineers, product managers, and customers, to understand their requirements and craft effective solutions. State-of-the-Art Pipelines and Architecture : Design, develop, deploy and operate high-quality production ELT pipelines and data architectures. Integrate data from various sources and formats, ensuring compatibility, consistency, and reliability. Design scalable architectures. Champion Data Best Practices : Proactively establish and advocate for best practices in performance, code quality, data validation, data governance, and discoverability across Adyen through mentoring, training, and knowledge sharing. High Quality Data and Code: Ensure data is accurate, complete, reliable, relevant, and timely. Implement rigorous te

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Design, build, and maintain scalable, reliable, and high-availability data platforms and data pipelines to support analytics and data-driven applications Collaborate closely with data scientists, analysts, product teams, and software engineers to translate business requirements into robust and reusable data solutions Own data modeling and data architecture design to ensure data consistency, accuracy, and long-term maintainability Develop and optimize both batch and real-time (streaming) data processing pipelines to improve performance and system stability Ensure data quality, data governance, and data security through monitoring, validation, and anomaly detection mechanisms Continuously improve existing data pipelines and platforms through performance tuning, cost optimization, and technical debt reduction Participate in technology selection for data platforms and tools (e.g., databases, cloud services, data processing frameworks) and promote engineering best practices Create and maintain technical documentation to support knowledge sharing and long-term system sustainability Mentor and support junior data engineers, contributing to the overall technical growth and engineering excellence of the team Stay current with emerging trends and technologies in data engineering and big data, and evaluate their potential adoption and business value Responsibilities include, but not limited to: <span

Data Engineer, Data Platform About the Role We are building out our Data Platform team at Sigma, with a relentless focus on developing data models that fuel trusted insights across the company. As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both internal and external (demo) use cases. Reporting to the Head of Data, this is a high visibility role with the opportunity to work on greenfield projects. If you’re a data engineer with a builder mindset, who wants to leverage a best-in-class stack, and genuinely is invested in Sigma’s mission, let’s chat! What You Will Be Doing Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma ( Tech we use : Fivetran, dbt, Snowflake, Sigma, Hightouch, Metaplane) Build foundational processes for scaling our demo asset data across various Cloud Data Warehouses Partner with our infrastructure engineering team to ensure high availability of all key data assets Build and scale our data governance policies Work cross functionally to accomplish all of the above! You’ll work across Product, Engineering, GTM—with users of all skills and levels Qualifications We Need Strong knowledge and experience of working with APIs and building data pipelines from various systems into Cloud Data Platforms (e.g., Snowflake, Databricks) Strong communication and collaboration skills. You will primarily partner with the Analytics and Infrastructure Engineering teams internally at Sigma; your ability to work and collaborate closely with them will be integral to your success. Experience deploying data governance frameworks with a scalable and repeatable process Ability to thrive in ambiguous environments and get stuff done. We move fast and iterate quickly, and we want you to feel empowered to do exactly that 3+ years of relevant experience working in a data eng

Data Engineer, Data Platform About the Role We are building out our Data Platform team at Sigma, with a relentless focus on developing data models that fuel trusted insights across the company. As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both internal and external (demo) use cases. Reporting to the VP of Data & Revenue Engineering, this is a high visibility role with the opportunity to work on greenfield projects. If you’re a data engineer with a builder mindset who wants to leverage a best-in-class stack, and genuinely is invested in Sigma’s mission, let’s chat! What You Will Be Doing Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma ( Tech we use : Fivetran, dagster, dlt, terraform, dbt, Snowflake, Sigma, Hightouch, Metaplane) Build foundational processes for scaling our demo asset data across various Cloud Data Warehouses Scale our terraform deployment across all of our Snowflake assets Continue to advance our data governance policies Work cross functionally to accomplish all of the above! You’ll work across Product, Engineering, GTM—with users of all skills and levels Qualifications We Need Strong knowledge and experience of working with APIs and building data pipelines from various systems into Cloud Data Platforms (e.g., Snowflake, Databricks) Strong communication and collaboration skills. You will primarily partner with the Analytics and Infrastructure Engineering teams internally at Sigma; your ability to work and collaborate closely with them will be integral to your success. Experience deploying data governance frameworks with a scalable and repeatable process Ability to thrive in ambiguous environments and get stuff done. We move fast and iterate quickly, and we want you to feel empowered to do exactly that 3+ years of relevant experience wor

Location Qualifications: This role is available for hybrid work (2 days on-site) from our office in Bucharest. About the position Our data platform powers customer-facing embedded analytics that thousands of users rely on daily. But we're going further: Showpad is building a Revenue Intelligence engine that transforms raw signals — CRM data, email threads, call transcripts, and content engagement — into prescriptive AI guidance. You will be a foundational architect of the unified data intelligence layer that makes this engine possible. You will participate in the design of our Medallion architecture, star schemas, and data governance frameworks — and critically, you will help define how structured and unstructured knowledge is modeled, connected, and retrieved. Your goal is to build a platform so robust and intuitive that other teams are empowered to build high-quality downstream models with speed and autonomy. What You’ll Do Shape how we model and connect revenue data — accounts, deals, contacts, content, and engagement signals — across both structured and semantic layers Design and evolve the ontology that defines how entities relate, enabling relationship-aware reasoning beyond what traditional joins can offer Build and maintain a Knowledge Graph that supports multi-hop inference and entity disambiguation across our Revenue Intelligence engine Own our retrieval architecture — choose the right approach for each use case, whether that's RAG, vector similarity, graph traversal, or structured search Define how we ground LLM outputs in proprietary data, ensuring AI features are accurate, explainable, and production-ready Contribute to our Medallion architecture, star schemas, and data catalog, keeping the foundation solid as we scale Ensure our embedded analytics meet the demands of multi-tenant isolation, sub-second latency, and strict SLAs for white-labeled products Be a go-to resource for cross-functional teams — setting standards, reviewing models, and helping oth

About Sapience AI Sapience AI is the collective intelligence platform for professional communities. We sit above the CRMs, AMS platforms, and knowledge bases that organizations already run, and we turn the expertise scattered across them into something every member can search, act on, and share. The intelligence a community needs is already inside it. Most organizations just cannot reach it. Knowledge lives in silos, in legacy systems, in the heads of a few experts, and in fragmented records no one can connect. We change that. Our work is grounded in four commitments: technology elevates people and never replaces them, the best expertise is already inside the community, everything is built on trust, and every deployment is purpose-driven for the organization it serves. Let’s achieve more, together. Where this role sits This role owns the shape of the data that AI learns from and reasons over. You design the data models, schemas, and representations that connect a community’s knowledge to the models, the KO graph, and the COGENT architecture. You work where data architecture meets machine learning: how knowledge is modeled, how features and embeddings are represented, and how data flows from raw sources to the systems that reason over it. You are the person who makes sure the data foundation is coherent, so everything built on top of it, from retrieval to reasoning to models, has something solid and consistent to stand on. Why this role exists AI is only as good as the data it learns from and reasons over. When data models are inconsistent or poorly designed, every system downstream inherits the mess, and trust erodes. Modeling data for collective intelligence is hard: it has to serve models, graphs, retrieval, and reasoning at once, across many communities, without fragmenting. The Senior AI/ML Data Model Architect owns that foundation. You design the data models and representations that keep the platform coherent and let every AI system built on them work well. Wha

ABOUT CAPCO Capco, a Wipro company, is a global management and technology consultancy specialising in driving digital transformation across the financial services industry. Operating at the intersection of business and technology, Capco combines innovative thinking with unrivalled industry knowledge to fast-track initiatives for banking and payments, capital markets, wealth and asset management, and insurance. Our ingenuity is brought to life through our Innovation Labs, award-winning Be Yourself at Work culture, and a diverse, talented team across more than 30 offices worldwide. ROLE DESCRIPTION As a Knowledge Graph & Ontologies Specialist, you will lead the design and delivery of enterprise knowledge graph and semantic ontology solutions for Capco's financial services clients across Asia. Based in Singapore, you will serve as a senior practitioner and trusted advisor to insurers, wealth managers, private banks, and capital markets firms — helping them realise the value of connected, semantically rich data. This is a hands-on, client-facing role. We are looking for someone who has built and deployed real-world knowledge graph solutions — ideally through experience at or with a graph technology vendor such as Stardog, Neo4j, Franz Inc. (AllegroGraph) or Ontotext (GraphDB), or through deep project delivery at a specialist consultancy. You will join a growing data and AI practice in Asia and will have the opportunity to shape Capco's knowledge graph capability, contribute to thought leadership, and build lasting client relationships at the most senior levels. KEY RESPONSIBILITIES Lead the design, development, and delivery of enterprise knowledge graph architectures and domain ontologies for financial services clients. Define and govern ontological models representing complex financial data domains including insurance products, policy hierarchies, client entities, wealth portfolios, regulatory obligations, and counterparty relationships. Advise clients on the

Data Engineer Description - Key Roles Designs and establishes secure and performant data architectures, enhancements, updates, and programming changes for portions and subsystems of data pipelines, repositories or models for structured/unstructured data. Analyzes design and determines coding, programming, and integration activities required based on general objectives and knowledge of overall architecture of product or solution. Writes and executes complete testing plans, protocols, and documentation for assigned portion of data system or component; identifies and debugs, and creates solutions for issues with code and integration into data system architecture. Collaborates within a project team of other data engineers to develop reliable, cost effective and high-quality solutions for assigned data system, model, or component. Analyzes data inaccuracies, identifies opportunities and supports the development of automated solutions to enhance overall quality of the enterprise data. Identifies problematic areas and conducts research to determine the best course of action to correct the data; identifies, analyzes and interprets trends and patterns in complex datasets. Works cross-functionally with different departments to assess, define, and develop report deliverables. Represents the software data engineering team for all phases of larger and more-complex development projects. Provides guidance and mentoring to less experienced staff members. Education & Experience Recommended Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, Statistics/ Mathematics, or any other related di

Capco, a Wipro company, is a global technology and management consultancy specializing in driving digital transformation in the financial services industry. With a growing client portfolio comprising of over 100 global organizations, Capco operates at the intersection of business and technology by combining innovative thinking with unrivalled industry knowledge to deliver end-to-end data-driven solutions and fast-track digital initiatives for banking and payments, capital markets, wealth and asset management, insurance, and the energy sector. Capco’s cutting-edge ingenuity is brought to life through its Innovation Labs and award-winning Be Yourself At Work culture and diverse talent. Role Summary As a Data Engineer (Intermediate/Senior) , you will work closely with Data Architects, Business Analysts, BI developers, and client technology teams to design and implement reusable data ingestion and transformation pipelines in Data Lake/Lakehouse implementation programme What You’ll Do Developing batch, CDC and/or streaming data ingestion pipelines from multiple source systems. Implementing Bronze, Silver and Gold data layers , including data cleansing, transformation and standardisation. Developing reusable data pipelines and supporting data product implementation. Implementing data quality, reconciliation, validation and monitoring controls. Supporting data migration, integration testing, UAT and production release. Working with the architecture team to ensure solutions follow agreed cloud, security, governance and engineering standards . Supporting knowledge transfer and BAU handover. What We’re Looking For 4+ years of experience in data engineering or related roles. Strong experience in Databricks, Azure, SQL, Python/PySpark, ETL/ELT, Delta Lake, data modelling, data quality and CI/CD. Experience in financial services especially asset management or large-scale data transformation, would be advantageous. Experience in workong on an end-to-end enterprise da

About the team The Applied team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the role: We're seeking a Data Engineer to take the lead in building our data pipelines and core tables for OpenAI. These pipelines are crucial for powering analyses, safety systems that guide business decisions, product growth, and prevent bad actors. If you're passionate about working with data and are eager to create solutions with significant impact, we'd love to hear from you. This role also provides the opportunity to collaborate closely with the researchers behind ChatGPT and help them train new models to deliver to users. As we continue our rapid growth, we value data-driven insights, and your contributions will play a pivotal role in our trajectory. Join us in shaping the future of OpenAI! In this role, you will: Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse. Develop canonical datasets to track key product metrics including user growth, engagement, and revenue. Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions. Implement robust and fault-tolerant systems for data ingestion and processing. Participate in data architecture and engineering decisions, bringing your strong experience and knowledge to bear. Ensure the security, integrity, and compliance of data according to industry and company standards. You might thrive in this role if you: Have 3+ years of experience as a data engineer and 8+ years of any software engineering experience(including data engineering). Proficiency in at least one programming language commonl

Capco, a Wipro company, is a global technology and management consultancy specializing in driving digital transformation in the financial services industry. With a growing client portfolio comprising of over 100 global organizations, Capco operates at the intersection of business and technology by combining innovative thinking with unrivalled industry knowledge to deliver end-to-end data-driven solutions and fast-track digital initiatives for banking and payments, capital markets, wealth and asset management, insurance, and the energy sector. Capco’s cutting-edge ingenuity is brought to life through its Innovation Labs and award-winning Be Yourself At Work culture and diverse talent. Role Summary As a Data Architect , you will lead the architecture and data design work, working closely with Data Engineers, Business Analysts, BI teams, and client technology and business stakeholder in the Data Lake/Lakehouse implementation project. What You’ll Do Designing the target Lakehouse architecture and end-to-end data flows. Defining data models, canonical structures and reusable data-product patterns . Designing scalable and reusable batch, CDC and streaming ingestion patterns . Establishing data architecture standards covering data quality, reconciliation, lineage, governance, security and access . Assessing and aligning the solution with existing enterprise and regional architecture standards. Supporting source-to-target mapping, data migration and integration design. Providing technical leadership and guidance to Data Engineering teams throughout implementation. Supporting solution design reviews, testing, production readiness and BAU handover. What We’re Looking For 6+ years of experience in data architecture, data engineering, or related roles. Strong expertise in Azure, Databricks, Delta Lake, data modelling, data architecture, data integration/ETL, data governance and cloud architecture. Experience designing enterprise data platforms and data products, particula

Education: Master or Bachelor’s degree in computer science, information systems management or related field. Solution and Architecture certifications such as TOGAF or other. Experiences: More than 12+ years of experience in information technology, with 8+ years spent in data architecture or technology solutions definitions and implementations. Extensive experience in banking and financial services domain Knowledge & Skills: Expertise in Data Architecture, Data Strategy and Roadmap for large and complex organization and systems and implemented large scale end-to-end Data Management & Analytics solutions Experience in transforming traditional Data Warehousing approaches to Big Data based approaches and proven track record of managing risks and data security Expertise with DW Dimensional modeling techniques, Star & Snowflake schemas, modeling slowly changing dimensions and role playing dimensions, dimensional hierarchies, and data classification Experiences in cloud native principals, designs and deployments. Extensive experience working with and enhancing Continuous Integration (CI) and Continuous Development (CD) environments Expertise in Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, and Data Archival Define workload migration strategies using appropriate tools Drive delivery in a matrixed environment working with various internal IT partners Demonstrated ability to work in a fast paced and changing environment with short deadlines, interruptions, and multiple tasks/projects occurring simultaneously Must be able to work independently and have skills in planning, strategy, estimation, scheduling, Strong problem solving, influencing, communication, and presentation skills, self-starter Experience with data processing frameworks and platforms (Informatica, Hadoop, Presto, Tez, Hive, Spark etc.) Hands-on experience with related/complementary open source software platforms and languages (e.g. Java, Linux, Python, GIT, Jenki

What you will be doing: Key responsibilities As a Data Engineer Intern, your role will encompass: ● Supporting to conduct ambitious projects in the transformation of clients through data ● Collaborating with the consulting and data team to provide comprehensive services to clients ● Using your technical abilities to assist in the transformation of clients’ marketing department Among your responsibilities as a Data Engineer Intern, you will be responsible for: ● Help securing delivery on projects with Data Engineer ● Communicating the success of projects among the company ● Working closely with your Consulting counterpart to build and maintain strong relationships with your clients and best understand their needs ● Ensuring that your solutions are bringing values to the client problematic ● Being a good team player, knowing your role and responsibility in the global ambition ● Caring for the happiness of the team, ensuring work is delivered to a high standard and providing feedback and mentoring Being a great tech person ● Demonstrating the skill and credibility required to ensure the success of our clients’ initiatives ● Researching and developing new technical approaches to address problems efficiently ● Sharing best practices and contributing to Artefact’s institutional knowledge ● Embodying Artefact’s values and inspiring others to do the same ● Experience working with Big Data technologies such as Hadoop, Spark, Kafka... ● Delivering Data Lake / Big Data projects including (data ingestion, machine learning model application, code deployment) ● Being able to adapt your solutions and approaches to technical environment (security, access, tools) Qualifications :Education and Experience ● Bachelor’s degree in Software Engineering, Computer Engineering, or related fields ● Solid knowledge of computer science, data processing and data architecture ● Intellectual curiosity and excellent problem-solving skills, including the ability to structure and prioritise an

Citi's Investor Services Technology group is seeking a technically exceptional and domain-savvy Data Architect to serve as the definitive data architecture authority across the Investor Services (IS) program — spanning Custody, Fund Administration, and Securities Finance. This is explicitly a hands-on architect role . The successful candidate will be expected to write, review, and validate architecture artifacts, data models, canonical schemas, and technical standards. You will be embedded with delivery teams, working directly with business analysts, data engineers, and technology leads to produce production-quality data architecture outputs that the entire IS program depends on. You will also lead the design and delivery of a suite of data architecture utilities — reusable tooling, accelerators, and automation that dramatically compress the time to deliver consistent, standards-compliant data integrations across Investor Services platforms. This role is a rare opportunity to set the data foundations for one of the most complex and consequential technology transformation programs in global financial services. Deep Custody and/or Fund Services domain knowledge is a prerequisite, not a preference. Responsibilities: Da ta Architecture Principles & Standards Define, document, and own the Investor Services data publication architecture principles — governing data modelling standards, naming conventions, versioning strategies, API data contracts, and data quality rules across all IS technology domains. Architecture Pattern Standardization Work with delivery leads across all 50&#43; IS platforms to define, document, and enforce standardized architecture patterns for data generation, transformation, and consumption — covering batch, near-real-time,