Senior Data Engineer

Job Summary

Serve as an Architect within a global enterprise designing and optimizing scalable data solutions using Python, Databricks SQL, and PySpark. Enable secure high-quality data products that support analytics and AI initiatives in a hybrid work model with day shifts and no travel requirement while aligning technical delivery to business value.

• Design advanced distributed data processing solutions using Python and PySpark to deliver reliable batch and streaming pipelines that support key business analytics needs
• Develop efficient Databricks SQL queries and curated datasets to empower data consumers with timely and trustworthy insights for strategic decision making
• Architect data models and data lake structures that promote reusability, governance and scalability across multiple domains and cross‑functional initiatives
• Optimize Spark jobs for performance, cost efficiency and stability by tuning configurations, partitioning strategies and storage formats on the Databricks platform
• Collaborate with product teams, data engineers and data analysts to translate complex business requirements into robust data architecture and implementation patterns
• Define standards and best practices for coding, testing, monitoring and documentation of Spark in Scala, Python, Databricks SQL and PySpark based solutions