Data Engineer - Business Intelligence

SchoolAI is seeking a skilled Data Engineer focused on Business Intelligence to design, build, and maintain our data infrastructure and pipelines. We believe in working as cross functional teams to build delightful products. You'll work closely with Product Management, Infrastructure Engineers, Data Scientists, Data Analysts, AI/ML Engineers, and other stakeholders to ensure efficient data delivery and processing across the organization.

An ideal candidate understands software development best practices and isn’t fooled into thinking that the outputs of what they build outweigh the outcomes of what they build. They’ll work well with others and be excited about the opportunity to work at a Series A stage startup.

About the role

• Design, develop, and maintain scalable ETL data pipelines, using modern data engineering tools and best practices
• Build and optimize data models and architectures to support analytics and business intelligence needs
• Implement data quality controls and monitoring systems to ensure data accuracy and reliability
• Collaborate with cross-functional teams, including folks in other departments, to understand data requirements and provide technical solutions
• Write efficient SQL queries and optimize database performance
• Deploy and maintain cloud-based data infrastructure
• Create and maintain technical documentation for data systems and processes
• Tools that you might work with here include: Segment, HubSpot, BigQuery, dbt, Airbyte, PostHog, Statsig, Hightouch, Fivetran and others

We'd love to hear from you if you have:

• A deep understanding of and extensive experience with distributed systems
• Built and maintained large scale ETL pipelines
• 3+ years of experience in data engineering or similar role
• Strong programming skills in Python, SQL, and shell scripting
• Experience with ETL tools and data pipeline orchestration (e.g., Airflow)
• Proficiency in working with both relational and NoSQL databases
• Experience with cloud platforms (GCP, AWS, or Azure)
• Knowledge of data warehousing concepts and dimensional modeling

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