Cloudbeds - Tech Lead Data Engineer

• Data Architecture & Modeling Ownership: Set and evolve our cloud data architecture on Snowflake. Own data model design across data products and marts, implementing flexible dimensional models (Star Schemas, SCDs, conformed dimensions) and documenting decisions through Architecture Decision Records (ADRs). • Data Architecture & Modeling Ownership: • Data Engineering Competency: Lead the end-to-end design and execution of data pipelines—owning ingestion, API integrations, custom connectors, ELT/ETL processes, and pipeline orchestration. • Data Engineering Competency: • DataOps & CI/CD Integration: Build upon our existing Git, CI/CD, and Jira workflows by embedding specialized data discipline—such as automated dbt testing on pull requests, environment isolation, automated credential management, and data deployment standards. • DataOps & CI/CD Integration: • Governance & Observability Strategy: Build upon and refine the initial foundations of our governance model. Evaluate, select, and implement scalable Data Catalog and Data Observability solutions to track data lineage, ensure freshness, monitor completeness, and automate failure alerting. • Governance & Observability Strategy: • Platform Efficiency & Cost Control: Continuously tune Snowflake query performance, clustering, and warehouse sizing to optimize execution times and compute spend. • Platform Efficiency & Cost Control: • Technical Mentorship & Agile Leadership: Raise the technical effectiveness of Analytical Engineers within our Agile planning framework through architectural guidance, design reviews, and constructive challenge. • Technical Mentorship & Agile Leadership: • Stack Modernization & Architecture Evolution: Continuously evaluate new tools, frameworks, and architecture patterns to modernize, optimize, and add flexibility to our data stack. • Stack Modernization & Architecture Evolution: • What Sets You Up for Success • Senior Hands-On Experience: Proven track record as a Senior Data Engineer, Data Architect, or Tech Lead in cloud data environments. • AI & Agent Readiness: Exposure to preparing data structures, semantic models, feature stores, and API/access layers for AI agents, machine learning pipelines, and automated LLM workflows. • AI & Agent Readiness: • Snowflake & dbt Mastery: Deep hands-on expertise administering, tuning, and modeling in Snowflake, alongside advanced mastery of dbt (macros, incremental models, custom tests, packages, and dbt-native CI/CD testing). • Snowflake & dbt Mastery: • Snowflake • Advanced SQL & Python Skills: Expert analytical SQL skills (query execution plan tuning, window functions, CTEs) and strong Python proficiency for data pipelines, scripting, and MLOps workflows. • Orchestration & Tool Evaluation: Practical experience with ingestion and orchestration engines (e.g., Matillion, Apache Airflow, Prefect, Dagster, Fivetran), with a strong ability to evaluate architectural trade-offs, performance, and costs when selecting or migrating platforms. • Orchestration & Tool Evaluation: • DataOps & Software Engineering Discipline: Experience operating with active Git and CI/CD pipelines, with a track record of extending these systems to include automated data testing, deployment validation, and secure credential rotation. • DataOps & Software Engineering Discipline: • Critical Thinking & Problem Decomposition: Tendency to question assumptions, gather full business context, form hypotheses, and rigorously evaluate outputs (especially for AI/ML outputs) before jumping to technical solutions. • Critical Thinking & Problem Decomposition: • Pragmatic Experimentation: Passion for building lightweight MVPs and Proofs of Concept (POCs) to evaluate new technologies, test architectural hypotheses, and modernize the data stack. • Pragmatic Experimentation: • Communication & Technical Influence: Business-level English fluency with the ability to articulate complex technical trade-offs clearly, mentor teammates, and collaborate effectively in a remote, globally distributed team. • Communication & Technical Influence: • Exposure to applied AI tooling (Snowflake Cortex, AI Classify, RAG workflows, LLM agents, MCP servers). • Familiarity with modern BI consumption tools like Sigma or workflow engines like n8n. • Sigma • Work Authorization: Please note that applicants must be currently authorized to work in the location where the position is located without requiring visa sponsorship. At this time, Cloudbeds is unable to provide sponsorship for work visas. • Work Authorization: • What to Expect - Your Journey with UsBehind Cloudbeds' revolutionary technology is a team redefining what's possible in hospitality. We're 650+ team members across 40+ countries, bringing together elite engineers, AI architects, world-class designers, hoteliers, and hospitality veterans to solve challenges others haven't dared to tackle. Our diverse team speaks 30+ languages, but we all share one language: a passion for innovation and travel. From pioneering breakthroughs in machine learning to revolutionizing how hotels operate, we're not just watching the future of hospitality unfold – we're coding it, designing it, writing it, and shipping it. If you're ready to work alongside some of the brightest minds in tech who are obsessed with using AI to transform a trillion-dollar industry, this is your chance to be part of something extraordinary. • What to Expect - Your Journey with Us • Learn more online at cloudbeds.com • Cloudbeds Awards: • Cloudbeds Awards: • Winner – Hotel Management Software | HotelTechAwards (2026) • Winner – Hotel Management Software • Overall 10 Best Places to Work | HotelTechAwards (2026) • Overall 10 Best Places to Work • Overall Top 10 Hotelier's Choice | HotelTechAwards (2026) • Overall Top 10 Hotelier's Choice • Finalist – Property Management Systems (PMS) & Channel Managers | HotelTechAwards (2026) • Finalist – Property Management Systems (PMS) & Channel Managers • Most Loved Workplace® Certified (2024) • Most Loved Workplace® Certified • Deloitte Technology Fast 500 (2024) • Deloitte Technology Fast 500