least two years of experience building and leading highly complex, technical engineering teams.
hands-on experience in Databricks
scalable and sustainable data engineering solutions using tools such as Databricks, Azure, Apache Spark, and Python. The data pipelines must be created, maintained, and optimized as workloads move from development to production for specific use cases.
managing distributed teams preferred.
working with ambiguity and multiple stakeholders.
working cross functionality with product management and directly with customers; ability to deeply understand product and customer personas.
on Azure Cloud platform
SQL knowledge
on orchestrating workloads on cloud
to set and lead the technical vision while balancing business drivers
experience with PySpark, Python programming
with APIs, containerization and orchestration is a plus
handling large and complex sets of data from various sources and databases
grasp of database engineering and design principles.
