4 to 6 years of experience in data engineering or a closely related discipline
Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
Hands-on experience building and operating data pipelines on Databricks or an equivalent AI-first data platform
Proficiency in Python and SQL; experience with dbt and Databricks Delta Live Tables (DLT) for real-time and near-real-time pipeline development
Experience designing and implementing data quality frameworks including schema validation, null and duplicate checks, referential integrity enforcement, and business rule assertions
Demonstrated ability to build end-to-end reconcilable pipelines where row counts, aggregates, and key metrics can be validated at every stage from source to Gold
Experience with relational and/or NoSQL databases, REST APIs, and cloud-based data services
Strong understanding of lakehouse architecture, data modeling, testing practices, and CI/CD pipelines for data workflows
Demonstrated ability to build and optimize Databricks Genie spaces and AI/BI dashboards for business consumption
Experience building, deploying, and optimizing AI agents, with the ability to use AI coding agents efficiently to accelerate development
Ability to understand business requirements, engage confidently with stakeholders, and translate those requirements into reliable data products
Strong communication and collaboration skills across both technical and non-technical audiences