- 5 years of experience in Databricks(key)
- Lead design and architecture of large-scale data infrastructure and pipelines (Data Lakehouse).
- Transform complex business requirements into automated, secure data solutions (ETL/ELT) primarily in Azure.
- Optimize data storage and compute costs across Databricks clusters and Data Lake.
- Troubleshoot and resolve production pipeline failures and data quality issues.
- Drive best practices in data governance, security, and pipeline reliability.
- Mentor and coordinate with global teams (data scientists, analysts, operations)
Required Skills & Experience:
- 5–8 years (often 8 in practice) in data engineering or platform roles.
- Expert hands-on experience with Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
- Deep SQL and data modelling skills (OLAP, OLTP, dimensional modelling).
- Proficiency in Python/Scala for Spark jobs and data transformation.
- Understanding of Azure Data Lake Storage optimizations and Azure resource cost tuning.
- Experience implementing CI/CD and IaC for data pipelines.
- Knowledge of data security/compliance (RBAC, encryption, GDPR principles).
Interested candidates can share their updated CV at [HIDDEN TEXT]