Data Engineer 2

Qualifications

• Experience & Education
• Bachelor’s degree in Computer Science, Information Systems, Mathematics, Statistics, or related quantitative discipline
• 2-5 years of experience in data engineering, data development, or related technical field
• Proven experience building ETL/data pipelines in production environments
• Experience with agile development methodologies and cross-functional teams
• Technical Skills & Competencies
• Programming: Intermediate Python skills including decorators, generators, object-oriented programming
• SQL: Solid SQL proficiency with query optimization and performance tuning experience
• Data Engineering: Experience with data orchestration platforms (Airflow, Azure Data Factory, SSIS, or similar)
• Big Data: Familiarity with Apache Spark, PySpark, or similar distributed processing frameworks
• Cloud Platforms: Hands-on experience with Azure, AWS, or GCP data services (Databricks, Azure Functions, Delta Lake, etc.)
• Data APIs & Semantic Layer: Familiarity with semantic layer tools (CubeJS or similar) for data access and analytics
• CI/CD: Understanding of continuous integration/deployment for data pipelines
• Design Patterns: Knowledge of software design patterns and their application in data engineering
• AI/Automation: Basic understanding of AI/automation tools and their integration into data workflows
• Core Competencies Assessment
• Technical Skills (40%): Built ETL/data pipelines, production experience, CI/CD knowledge, AI/automation awareness
• Problem-Solving (25%): Production pipeline experience, architecture basics, scalability awareness
• Communication (20%): Agile team experience, stakeholder communication, cross-functional work
• Learning & Growth (15%): AI/automation project exposure, learning track record, business understanding

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