Staff Data Engineer / Full‑Stack Data Developer (Databricks / Python)
Core
Design, build, optimize, and operate data pipelines, curated data products, and Databricks-native data applications on a modern cloud Lakehouse platform to enable enterprise analytics, BI, AI/ML, and data-driven applications.
Role type
Staff Data Engineer / Full-Stack Data Developer
Builds
Scalable ETL/ELT pipelines, curated data layers (Bronze/Silver/Gold), reusable data transformation frameworks, Databricks-native data applications, dashboards, and data APIs.
Domain
Cloud Data Engineering / Lakehouse Architecture
Required skills
Python, Apache Spark (PySpark), Databricks, SQL, Data Structures and algorithms, Data quality and governance, Production support and operations, Technical leadership and mentorship
Preferred skills
AWS cloud services, Unity Catalog, Streaming data pipelines, CI/CD and Data/Analytics DevOps, BI and AI/ML enablement
Technologies
Databricks, PySpark, SQL, AWS (S3, IAM, EC2, Glue), Unity Catalog, Kafka
Responsibilities
Design and develop scalable ETL/ELT pipelines using Databricks and PySpark; Build and manage curated data layers following Lakehouse Medallion architecture; Develop Databricks-native data applications, notebooks, and dashboards; Optimize Apache Spark jobs for performance, cost efficiency, and scalability; Own and support production data pipelines and applications; Act as a technical leader defining best practices and influencing architecture.
Seniority
Staff, hands-on IC with technical leadership