Senior Data Engineer

5-8 years of professional experience building and operating production data systems. Strong hands-on expertise in Python. Ability to write clean, idiomatic, and maintainable Python code. Strong foundation in software engineering best practices (code reviews, documentation, testing, CI/CD). 6+ years of experience designing and modeling data in relational and non-relational databases. Experience working with modern data warehouses (dimensional modeling, ELT, query optimization). Hands-on experience building, scheduling, and monitoring batch data pipelines using Airflow or comparable tools. Strong understanding of data architecture fundamentals in cloud-based systems. Practical experience with AWS (core data and infrastructure services). Production experience with Snowflake (schema design, performance tuning, cost-aware usage). Experience working with sensitive or regulated data and compliance requirements (HIPAA, GDPR, CCPA). Ability to independently own and deliver data engineering projects with minimal supervision. Comfortable supporting high-priority data requests and operational issues. Proficiency with Python, SQL (MySQL/Snowflake), Airflow, AWS, and Terraform. Experience with distributed data processing tools such as Apache Spark (Nice-to-Have). Familiarity with serverless architectures (e.g., AWS Lambda) (Nice-to-Have).

Own end-to-end design, build, and operation of core data infrastructure. Lead rebuild and stabilization of core data pipelines. Build and operate data pipelines using modern data engineering stack. Act as senior technical contributor, establishing best practices. Partner cross-functionally to translate business needs into data solutions. Improve developer and analyst productivity. Drive continuous improvement of metrics and experimentation systems. Ensure data systems are designed and operated with privacy, security, and compliance. Support high-priority business initiatives by delivering accurate data quickly.