Sr. Databricks Engineer (Databricks + Spark + Azure)

Responsibilities
Design, develop, and maintain data pipelines using Databricks and Spark, and other cloud technologies as needed
Optimize data pipelines for performance, scalability, and reliability
Ensure data quality and integrity throughout the data lifecycle
Collaborate with data scientists, analysts, and other stakeholders to understand and meet their data needs
Troubleshoot and resolve data-related issues, and provide root cause analysis and recommendations
Document data pipeline specifications, requirements, and enhancements, and communicate them effectively to the team and management
Create new data validation methods and data analysis tools, and share best practices and learnings with the data engineering community
Implement ETL processes and data warehouse solutions, and ensure compliance with data governance and security policies

Qualifications
Bachelor's degree in Computer Science, Engineering, or related field, or equivalent work experience
5+ years of experience in data engineering with Databricks and Spark
Proficient in SQL, Python and PySpark
Experience with Azure Databricks Medallion Architecture with DLT, Iceberg
Financial/Corporate Banking context would be a plus
Experience with data integration and ETL tools, such as Azure Data Factory
Experience with Azure cloud platform and services
Experience with data warehouse and data lake concepts and architectures
Good to have experience with big data technologies, such as Kafka, Hadoop, Hive, etc
Strong analytical and problem-solving skills
Excellent communication and teamwork skills