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Tech Stack
Tools & technologiesBigQueryCloudETLGoogle Cloud PlatformPythonSQL
About the role
Key responsibilities & impact- Build and support non-interactive (batch, distributed) & real-time data pipelines
- Build fault-tolerant, self-healing, adaptive, and highly accurate data computational pipelines
- Provide consultation and lead implementation of complex programs
- Develop and maintain documentation for assigned systems and projects
- Tune queries over billions of rows of data in a distributed query engine
- Perform root cause analysis for software/business process issues
- Implement and maintain dbt transformation models, CI pipelines, data contracts
- Build and monitor data quality gates and freshness SLOs
- Optimize BigQuery cost and performance with query tuning, storage design
- Implement platform hardening controls including retries, dead-letter queues
Requirements
What you’ll need- Strong background in data engineering
- Hands-on experience in Google Cloud Platform (GCP) services such as Pub/Sub, Dataflow, and BigQuery
- Proficiency in SQL and Python
- Familiarity with moving/transforming data across cloud-based data zones and streaming pipelines (ETL/ELT)
- Comfort with cloud services, data management, automation tools, and real-time data processing
- Advanced English skills
Benefits
Comp & perks- growth opportunities
- values-driven culture
- international careers
- opportunity to shape the future of experience
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringSQLPythonETLELTquery tuningdata transformationdata qualityroot cause analysisdata pipeline development
Soft Skills
consultationleadershipdocumentationproblem-solvingcommunicationadaptabilityorganizational skillsattention to detailcollaborationanalytical thinking
