Data Engineer

• Design, develop, and maintain scalable data pipelines that ingest, process, and transform structured and unstructured data
• Write advanced SQL queries—including complex joins, aggregations, window functions, and CTEs—to support ETL, data analysis, and migration projects
• Develop, optimize, and productionize Python scripts for data movement and validation using vanilla Python
• Collaborate across teams to deliver robust APIs and services for data integration with frontend (React, Angular, Vue) and backend (Node.js, Express) frameworks
• Architect and maintain data models and schemas, ensuring alignment with business requirements and efficient data retrieval
• Manage production-level SQL (e.g., SQL Server) and NoSQL (e.g., MongoDB) databases
• ensure data quality through continuous monitoring and rigorous testing
• Deploy and manage automated ETL pipelines and schema migrations using Azure Data Factory, Microsoft Fabric, or comparable technologies
• Continuously improve performance through query optimization and efficient use of data structures (lists, dictionaries, sets) in Python
• Implement agile methodologies, continuous delivery, and DevOps best practices for reliable and scalable data infrastructure
• Enforce rigorous data quality management and automated testing strategies to ensure accuracy and reliability of data assets

• 5+ years data engineering experience
• Advanced proficiency in SQL (SELECT statements, joins, aggregations, subqueries, window functions, CTEs, DML statements, schema design, and query optimization)
• Strong experience in Python (native/vanilla), effectively leveraging core data structures for data manipulation
• Demonstrated ability to build production-level scripts/services in JavaScript/TypeScript and Python
• hands-on with frontend (React, Angular, Vue) and backend (Node.js, Express) frameworks
• Proven expertise with Azure Data Factory, Microsoft Fabric, or other enterprise-grade data platforms
• Extensive work with both SQL and NoSQL databases (SQL Server, MongoDB), including schema modeling, complex querying, and troubleshooting data migrations
• Comfort maintaining projects in Git/GitHub
• experience in automated deployments, CI/CD, and schema migrations
• Solid foundation in agile development, continuous delivery, and designing/maintaining RESTful APIs (security, testing, performance, JSON)
• Deep understanding of data quality, test strategy development, and test automation in data solutions

PySpark experience is a plus

• medical, vision, dental, and life and disability insurance
• eligible to enroll in our company 401(k) plan
• free online training