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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and maintaining scalable analytics data models, implementing data quality checks, and collaborating with cross-functional teams to deliver intuitive data products. Proficient in SQL, Python, and analytics transformation frameworks to ensure reliable data pipelines and effective business intelligence solutions.
Highest-signal resume keywords
Analytics EngineeringSQL ProficiencyData Quality TestingData Transformation FrameworksDimensional Modeling
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
SQLPythonDimensional ModelingData Quality TestingData TransformationData Pipeline ManagementAnalytics Data ModelsData GovernanceObservabilityDocumentation
Soft Skills
Strong CommunicationProblem-SolvingOrganizational Skills
Tools & Technologies
DbtSnowflakeDatabricksBigQueryRedshift
Industry Keywords
Business IntelligenceData EngineeringData CatalogingData LineageData Security
Tech Stack
Tools & technologiesAmazon RedshiftBigQueryPythonSnowflakeSQL
About the role
Key responsibilities & impact- Design, develop, and maintain scalable analytics data models for reporting, business intelligence, product analytics, and operational decisions
- Build and manage trusted data pipelines and transformation workflows
- Partner with Engineering, Product, Design, Strategy & Operations, AI Platform, and business stakeholders
- Establish definitions, metrics, dimensions, and data contracts
- Develop reusable datasets and semantic models for self-service analytics
- Improve reliability, performance, observability, and maintainability of analytics infrastructure
- Implement data quality checks, testing, documentation, lineage, and monitoring
- Collaborate with data engineers and platform teams on data architecture, warehouse performance, and transformation workflows
- Ensure data products are intuitive, discoverable, and fit for purpose
- Establish analytics engineering best practices, including version control, code review, CI/CD, documentation, and deployment standards
- Communicate technical concepts to technical and non-technical audiences
Requirements
What you’ll need- 4+ years of experience in analytics engineering, data engineering, business intelligence engineering, or a related field
- Strong SQL skills, including complex queries and dimensional data models
- Experience with dbt or comparable analytics transformation frameworks
- Proficiency in Python or another programming language for data processing and automation
- Experience with Snowflake, Databricks, BigQuery, or Redshift
- Understanding of dimensional modeling, fact and dimension tables, slowly changing dimensions, and semantic layers
- Experience with data quality testing, monitoring, documentation, and observability
- Ability to translate ambiguous business questions into scalable data solutions
- Strong communication, problem-solving, and organizational skills
- Understanding of data governance, security, privacy, and responsible data use
- Familiarity with data cataloging and lineage tools
Benefits
Comp & perks- Equal employment opportunities regardless of protected status
- Qualified candidates with criminal histories considered in accordance with legal requirements