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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in architecting and evolving data platforms, with a strong focus on data transformations, data warehousing, and real-time processing. Proven ability to mentor teams and drive high-quality data products that empower business insights.
Highest-signal resume keywords
Data Platform ArchitectureData Transformations Using DbtBack-End Engineering (NodeJS, Python, Java, C#)Infrastructure as Code (Terraform)Data Warehousing and Data Lake Implementations
ATS Keywords
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Hard Skills
Data Platform ArchitectureData Transformations Using DbtData WarehousingData Lake ImplementationsBack-End EngineeringData PipelinesStreamingData ValidationQuality Assurance PracticesIncident Response
Soft Skills
MentoringCollaborationInfluencing Decisions
Tools & Technologies
SQLNoSQLTerraformDockerKubernetes
Industry Keywords
Data EmpowermentHigh-Velocity Development PracticesAutomated Batch Processing SystemsReal-Time Processing SystemsCross-Functional Collaboration
Tech Stack
Tools & technologiesCloudDockerJavaKubernetesNode.jsNoSQLPythonSQLTerraform
About the role
Key responsibilities & impact- Architect, design, and evolve a world-class data platform
- Lead the development of the analytics and semantic layer
- Drive self-service data empowerment through high-quality data products
- Mentor and guide a team of data and software engineers
- Collaborate with cross-functional teams to understand data needs
- Influence key business and technical decisions regarding data platform architecture
- Champion modern, high-velocity development practices in data processes
- Enable product teams to generate insights driving business success
Requirements
What you’ll need- Significant experience in building and maintaining data platforms based around dbt
- Proven track record of designing robust data architectures
- Experience with data warehousing, data lake implementations, and both real-time and batch processing systems
- Proficient in data transformations using dbt
- Familiar with data storage technologies (SQL / NoSQL)
- Experience in back-end engineering (NodeJS / Python / Java / C#)
- Understanding of data pipelines, streaming, and CDCs
- Knowledge of data validation and quality assurance practices
- Familiarity with cloud-native, containerized, or automated batch processing systems
- Understanding of incident response and RCA for data systems
- Experience with infrastructure as code (Terraform) and containerization (Docker, Kubernetes)
Benefits
Comp & perks- Health insurance
- Flexible working hours
- Professional development opportunities
- Equal opportunity employer committed to diversity and inclusion