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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and documenting instrumentation standards, building scalable analysis pipelines, and utilizing AI to enhance data workflows. Proficient in SQL and Python, with a strong focus on data quality, discoverability, and effective communication of insights.
Highest-signal resume keywords
SQLPythonData Workflow OrchestrationAI Utilization in EngineeringData Quality Assurance
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Analytics EngineeringData SolutionsNested Data StructuresWindow FunctionsQuery OptimizationData PartitioningETL/ELT PipelinesDAG DependenciesData ValidationTechnical Documentation
Soft Skills
Critical EvaluationCommunicationOwnershipIntegrityCollaboration
Certifications & Qualifications
Bachelor's Degree in Computer ScienceBachelor's Degree in StatisticsBachelor's Degree in Mathematics
Industry Keywords
Data-Driven EnvironmentProduct EngineeringData ScienceBusiness IntelligenceSelf-Service Data Access
Tech Stack
Tools & technologiesETLPythonSQL
About the role
Key responsibilities & impact- Develop and document instrumentation and experimentation standards
- Partner with product engineering teams to apply standards to priority product development work
- Build and improve scalable analysis pipelines and tooling
- Produce reliable insights and strengthen understanding of data structures and metrics
- Create tools and processes for self-service access to trusted datasets, insights and metric definitions
- Identify data quality and discoverability gaps and advocate for targeted improvements
- Maintain documentation for tools, datasets, metrics and operating practices
- Partner with Product, Engineering, Data Science, Data Engineering and Business Intelligence teams
- Communicate actionable insights and inform product improvements
- Use AI to accelerate analysis, prototyping and iteration while verifying correctness, quality and responsible use
Requirements
What you’ll need- Minimum of 2 years of experience delivering analytics engineering or data solutions in a fast-paced, data-driven environment
- Experience using SQL and Python, R or a comparable programming language with large, high-dimensional datasets
- Knowledge of nested data structures, window functions, query optimization and data partitioning
- Experience building and operating data workflows, including workflow orchestration, ETL/ELT pipelines and DAG dependencies across complex datasets
- Experience translating open-ended partner needs into clear, impactful technical objectives
- Demonstrated ability to use AI to improve speed and quality in day-to-day engineering workflows
- Ability to critically evaluate and verify AI-assisted work through testing, data validation, source-checking or peer review
- High integrity and ownership when protecting sensitive data and making final decisions
- Bachelor's degree in Computer Science, Statistics, Mathematics or a related discipline, or equivalent experience
Benefits
Comp & perks- Equity eligibility
- Flexible working model
- In-person office collaboration only 1–2 times per month
- Equal opportunity employment
- Medical or religious accommodation during the application process