Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Marketplaces Data and AI Org is a group of passionate machine learning, data, and analytics engineers responsible for creating new data products that drive quality, understanding and bookings. You’ll be part of the overall Guest and Host organization that is responsible for the Airbnb web and native apps used by hundreds of millions of our guests and Hosts. The Users and Contextualization Data & AI team, a vital part of the Marketplace Data & AI, focuses on building foundational data and systems to provide Airbnb teams with a deeper understanding of key domains. Specifically, this team concentrates on user data (Guest & Host), aiming to create high-quality, foundational, and well-governed user data and insights. These insights are crucial for enabling personalized and context-aware experiences that enhance trip quality both on and off the Airbnb platform, ultimately helping Airbnb better understand and serve its users throughout their journey. The Difference You Will Make: The quality of data related to Users, Listings, and Marketplaces is foundational to Airbnb's success, directly impacting our products and business. To enhance our data foundation and maximize the value derived from our data and machine learning models, we are significantly expanding our Data Engineering efforts in these crucial areas. A key opportunity lies in deepening our understanding of Airbnb users to improve the experience for both Hosts and Guests. As a Data Engineer focusing on this area, you will be responsible for executing these initiatives. This involves close collaboration with backend and analytics teams, product partners, and other data and ML engineers. Furthermore, you will have the chance to work directly with ML engineers on developing integrated NRT data and machine learning solutions. Ultimately, your contributions will lead to a better comprehension of Airbnb users and enhance their overall end-to-end product experience. A Typical Day: - Architect and productionize batch and real-time data systems to power products for Airbnb Guests and Hosts, or our business/sales teams. - Ensure the quality, performance, and stability of data systems with thoughtful quality systems and monitoring - Tune, productionize, and optimize data systems powering Airbnb products - Collaborate with product teams to extract data requirements from product specs to develop scalable and flexible systems - Collaborate and build relationships with partner engineering including backend/client, data science, analytics, and ML Your Expertise: - 9+ years of relevant industry experience with a Bachelor’s and/or Master’s degree in CS/EE, or equivalent experience, or 6+ years of experience with a PhD - Experience collaborating with client, backend, ml, analytics teams, product and business partners - Experience designing and deploying high performance Batch & NRT systems with reliable monitoring and logging practices. - Effectively work across team boundaries to establish overarching data architecture, data flow, and provide guidance to individual teams. - Strong knowledge of relational databases and query authoring (SQL) and streaming solutions. - Strong expertise with Python / Scala / Spark and operating on data at the petabyte scale. - Excellent communication skills, both written and verbal. Your Location: This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from. Our Commitment To Inclusion & Belonging: Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply. We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application. How We'll Take Care of You: Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits. Pay Range $204,000—$255,000 USD

Role Description We are looking for a Data Architect to join our teams and work on an international data modernization program. The successful candidate will play a central role in the design and development of the data architecture around Microsoft Fabric and Azure services, as well as in the technical consistency of several interconnected data scopes. Responsibilities - Define and develop the target data architecture based on Microsoft Fabric, Azure, and modern best practices (lakehouse, analytical warehouses, real time, etc.); - Design architectures for data collection, transformation, storage, and exposure adapted to large volumes and multiple business domains with the goal of creating an “AI Ready” environment; - Ensure consistency and interoperability between the program's various data areas (modeling, standards, component reuse); - Oversee technological choices and implementation patterns for data engineering teams (partitioning, optimization, governance, performance); - Contribute to the definition of data quality, security, and governance standards (traceability, cataloging, compliance, RBAC, etc.); - Participate in the scoping, design, and architecture review phases, and provide support during key migration and delivery phases; - Collaborate with business and IT stakeholders to align functional requirements, technical constraints, and target trajectory; - Work in an agile environment (SAFe type) with several distributed teams and multi-country challenges. Qualifications - Global vision and ability to structure a complex data landscape in a Microsoft Fabric & Azure environment, while remaining pragmatic; - Excellent communication, popularization, and negotiation skills with a variety of stakeholders (business, IT, security, architecture); - Technical leadership and a taste for collaborative work with multidisciplinary teams; - Comfortable in an international and multi-country context (Canada, United States, Europe, etc.); - Analytical mind, sense of prioritization, and results-oriented; - Excellent communication skills in French and English. English is required, as the position involves communicating with clients and colleagues located outside Quebec. Requirements - Solid experience in data architecture on cloud platforms, ideally Microsoft Azure (Azure Data Lake Storage, Azure Synapse/SQL, integration services, analytics, etc.); - Very good knowledge of Microsoft Fabric and its main workloads (Data Warehouse, Lakehouse, Data Engineering, Data Factory, Power BI, Real-Time Analytics, OneLake); - Proficiency in lakehouse architectures and medallion patterns (bronze/silver/gold) on OneLake or similar architectures; - Hands-on experience modernizing or migrating existing analytical environments to Microsoft Fabric or a new unified data platform (migrations of pipelines, notebooks, warehouses, models); - Good command of SQL and at least one distributed processing or scripting language (Spark, PySpark, T-SQL, KQL, DAX as needed); - Good knowledge of DataOps/DevOps data practices (CI/CD, pipeline industrialization, automated testing, observability, monitoring); - Understanding of data governance, quality, and security issues in a unified analytics platform context (catalog, metadata, lineage, security, compliance); - Assets: Microsoft Fabric/Azure data certifications (Fabric Analytics/Data Engineer Associate, Azure Data Engineer, etc.). Experience - Minimum 7 years of experience in the data field, including several years in an architect or technical data lead role; - Proven experience in large-scale cloud environments, preferably on Azure and, ideally, projects involving Microsoft Fabric; - Experience in a multi-team and multi-country context, with frequent interactions with various stakeholders. Benefits - Minimum of 3 weeks of vacation starting from the first year; - Comprehensive group insurance with a generous employer contribution; - Employer contribution to a group RRSP; - Full remote work flexibility: Hybrid, Remote, or On-site; - A warm, bright, and welcoming office offering fresh fruit, coffee, beverages, occasional meals, etc.; - Annual IT equipment budget; - A balanced work environment with flexible working hours; - Career development: training and certifications, online or in-person learning, Wepoint Academy, etc.; - An international community of experts ready to share their knowledge; - A company culture focused on individuals’ needs and their belonging to a strong community.

Role Description Drive technical implementation and testing of complex data pipeline features within the SPECTRA platform. Ensure robust end-to-end functionality and meet project release timelines. - Design and develop data processing pipelines using SQL and Python. - Handle large-scale data collection, transformation, and quality monitoring workflows. - Build and maintain dashboards and visualization tools. - Provide visibility into data quality, rater performance, and platform metrics for stakeholders across multiple teams. - Create comprehensive end-to-end tests and monitoring alerts. - Ensure platform reliability, data integrity, and proactive identification of issues in the data collection workflow. - Debug and troubleshoot complex data flow issues across the SPECTRA platform. - Identify root causes and implement solutions to maintain high system availability. - Collaborate closely with Technical Leads and engineering teams. - Implement backend data processing logic and ensure adherence to development standards and best practices. Qualifications - Experience in SQL development writing complex queries, data transformations, and working with large datasets in production environments. - Proficient in Python with experience in data processing, automation, and pipeline development using object-oriented programming principles. - Experience with data engineering pipelines including ETL processes, data modeling, and building scalable data processing workflows. - Hands-on experience with data visualization and dashboard tools such as Tableau or similar platforms. - Strong analytical and problem-solving skills with demonstrated ability to debug complex data issues and implement effective solutions. - Experience with data quality monitoring and automated testing frameworks. Requirements - Degree in Computer Science or related field. - Machine Learning experience with understanding of ML model training data requirements, feature engineering, and model evaluation metrics. - Experience building and scaling large products or systems. - Experience with building privacy and ads-related products. - Experience working with human labeling and annotation systems including workflow design, quality assurance, and vendor management in data collection operations. - Prior experience working with the company or its internal tools. Benefits - Compensation: $70–$95/hour. - Remote work opportunity. Application Process - Upload resume. - AI interview based on your resume. - Submit form. For details about the interview process and platform information, please check: Interview Process Details For any help or support, reach out to: support@mercor.com PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

• ETL/ELT Data Pipelines: Leading the design, development, and maintenance of robust ETL/ELT data pipelines. • SQL Queries: Writing, optimising, and reviewing advanced SQL queries for data extraction and transformation. • Data Workflows: Implementing and managing sophisticated data workflows and dependencies using tools like Airflow. • Data Models and Warehouses: Designing, building, and maintaining advanced data models and data warehouses using Snowflake, BigQuery and similar technologies. • Cross-functional Collaboration: Collaborating with cross-functional teams to understand complex data requirements and deliver efficient solutions. • Data Quality: Ensuring high data quality, integrity, and security across the data lifecycle. • Platform and Process Improvement: Continuously improving data engineering processes and infrastructure, implementing best practices, and ensuring our platform is performant, secure, and cost-efficient. • Pipeline Improvement: Design, develop, and maintain automated ML pipelines alongside our data scientists to streamline model training, validation, and deployment processes. • AI Champion: You actively leverage AI tools to accelerate your own output and you help to drive wider productivity and efficiency gains through mentoring and knowledge sharing. • Data Governance: Partner with our Security and Legal teams to implement automated data masking, PII management, and access control policies, and lead the implementation of data catalogs and lineage tracking to ensure data is discoverable, documented, and trusted across the entire Carwow Group.