[Hiring] Tech Lead Data Engineer @Cloudbeds

Role Description

As our Tech Lead Data Engineer & Data Architect , you will shape the technical direction, architectural standards, and data governance of our core Data Analytics platform. This is a hands-on leadership role:

• Act as our Data Architect—owning logical and physical data modeling, warehouse design, and layered curation (staging → intermediate → mart).
• Help continuously modernize our tech stack, elevating our software engineering discipline across our data pipelines (DataOps/CI-CD).
• Optimize compute performance and costs, drive MLOps workflows, and reinforce data quality and security standards.
• Drive our AI-readiness initiatives—architecting the semantic layers, data structures, and access patterns needed for AI agents and automated workflows.
• Serve as the technical anchor for a talented team of Analytical Engineers, collaborating closely with Engineering, Infrastructure, Data Science / ML, and business stakeholders.

Qualifications

• Proven track record as a Senior Data Engineer, Data Architect, or Tech Lead in cloud data environments.
• Exposure to preparing data structures, semantic models, feature stores, and API/access layers for AI agents, machine learning pipelines, and automated LLM workflows.
• 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).
• Expert analytical SQL skills (query execution plan tuning, window functions, CTEs) and strong Python proficiency for data pipelines, scripting, and MLOps workflows.
• Practical experience with ingestion and orchestration engines (e.g., Matillion, Apache Airflow, Prefect, Dagster, Fivetran).
• 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.
• Tendency to question assumptions, gather full business context, form hypotheses, and rigorously evaluate outputs (especially for AI/ML outputs).
• Passion for building lightweight MVPs and Proofs of Concept (POCs) to evaluate new technologies, test architectural hypotheses, and modernize the data stack.
• 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.

Requirements

• 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).
• Lead the end-to-end design and execution of data pipelines—owning ingestion, API integrations, custom connectors, ELT/ETL processes, and pipeline orchestration.
• Build upon our existing Git, CI/CD, and Jira workflows by embedding specialized data discipline.
• Build upon and refine the initial foundations of our governance model.
• Continuously tune Snowflake query performance, clustering, and warehouse sizing to optimize execution times and compute spend.
• Raise the technical effectiveness of Analytical Engineers within our Agile planning framework through architectural guidance, design reviews, and constructive challenge.
• Continuously evaluate new tools, frameworks, and architecture patterns to modernize, optimize, and add flexibility to our data stack.

Benefits

• Remote First, Remote Always.
• PTO in accordance with local labor requirements.
• Fully Paid Parental Leave.
• Home office stipend based on country of residency.
• Professional development courses in Cloudbeds University.
• Access to professional development, including manager training, upskilling, and knowledge transfer.