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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Data Engineering and Architecture, with a strong focus on Snowflake optimization, dbt implementation, and data pipeline orchestration. Proven ability to lead technical teams, mentor peers, and drive AI-readiness initiatives within cloud data environments.
Highest-signal resume keywords
Snowflake AdministrationAdvanced Dbt MasteryExpert Analytical SQL SkillsPython ProficiencyData Pipeline Orchestration
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ModelingData Warehouse DesignELT/ETL ProcessesAPI IntegrationsData GovernanceData Catalog SolutionsData ObservabilityQuery Performance TuningMLOps WorkflowsLightweight MVP Development
Soft Skills
Critical ThinkingCollaborationMentorshipCommunicationBusiness-Context Gathering
Tools & Technologies
GitCI/CDJiraMatillionApache AirflowPrefectDagsterFivetranAutomated TestingCredential Management
Industry Keywords
Cloud Data EnvironmentsData Analytics PlatformAI AgentsMachine Learning PipelinesData Structures
Tech Stack
Tools & technologiesAirflowApacheCloudETLMatillionPythonSnowflakeSQL
About the role
Key responsibilities & impact- Shape the technical direction, architectural standards, and data governance of the core Data Analytics platform
- Own logical and physical data modeling, warehouse design, and layered curation from staging to intermediate to mart
- Serve as Data Engineering Tech Lead and technical anchor for Analytical Engineers
- Lead end-to-end design and execution of data pipelines, including ingestion, API integrations, custom connectors, ELT/ETL processes, and pipeline orchestration
- Embed specialized data discipline into Git, CI/CD, and Jira workflows
- Implement automated dbt testing, environment isolation, credential management, and data deployment standards
- Build and refine governance foundations
- Evaluate and implement Data Catalog and Data Observability solutions for lineage, freshness, completeness, and failure alerting
- Tune Snowflake query performance, clustering, and warehouse sizing to optimize execution times and compute spend
- Provide architectural guidance, design reviews, and technical mentorship within an Agile planning framework
- Evaluate tools, frameworks, and architecture patterns to modernize and optimize the data stack
- Drive AI-readiness initiatives through semantic layers, data structures, and access patterns for AI agents and automated workflows
- Collaborate with Engineering, Infrastructure, Data Science/ML, and business stakeholders
Requirements
What you’ll need- 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
- Advanced mastery of dbt, including macros, incremental models, custom tests, packages, and dbt-native CI/CD testing
- Expert analytical SQL skills, including query execution plan tuning, window functions, and CTEs
- Strong Python proficiency for data pipelines, scripting, and MLOps workflows
- Practical experience with ingestion and orchestration engines such as Matillion, Apache Airflow, Prefect, Dagster, or Fivetran
- Ability to evaluate architectural trade-offs, performance, and costs when selecting or migrating platforms
- Experience operating with active Git and CI/CD pipelines, including automated data testing, deployment validation, and secure credential rotation
- Critical thinking, business-context gathering, hypothesis formation, and rigorous evaluation of outputs
- Experience building lightweight MVPs and proofs of concept
- Business-level English fluency
- Ability to articulate complex technical trade-offs, mentor teammates, and collaborate effectively in a remote, globally distributed team
Benefits
Comp & perks- 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