7+ years of overall experience in Data Engineering or a related data technology role.
Minimum 5 years of hands-on Databricks experience, including data engineering and/or Databricks infrastructure.
Mandatory understanding of Data Governance concepts, including data quality, metadata management, data lineage, data cataloging, data ownership, and access controls.
Practical knowledge of data governance principles and their application in data platforms.
Understanding of data governance frameworks, policies, standards, and data management best practices.
Experience or knowledge of implementing data quality checks, data lineage tracking, metadata documentation, and governed data access.
Strong expertise in Python, PySpark, and Advanced SQL.
Hands-on experience with the Databricks Lakehouse Platform, Delta Lake, Unity Catalog, Workflows, Jobs, Clusters, and Notebooks.
Experience developing ETL/ELT pipelines, data transformations, batch processing, and incremental data loading.
Good understanding of data warehousing and data modeling concepts.
Knowledge of data security, access management, and governance practices within data platforms.
Experience with Spark performance tuning, partitioning, file optimization, and query optimization.
Familiarity with Git, CI/CD practices, and production deployment processes.
Strong analytical, problem-solving, and communication skills.
We are proud to offer a competitive salary alongside a strong insurance package. We pride ourselves on the growth of our employees, offering extensive learning and development resources.