Description

Key Responsibilities
Design and implement scalable data platforms using Azure Databricks, Apache Spark, Delta Lake, and MLflow
Lead migration initiatives from legacy data platforms to Lakehouse Architecture
Build robust batch and real-time streaming pipelines for data ingestion, transformation, and analytics
Define and enforce data governance, security, and quality standards
Collaborate with business and technical stakeholders to deliver scalable data solutions
Mentor data engineers and establish Databricks engineering best practices
Integrate Databricks with Azure Data Factory, Kafka, Snowflake, Power BI, and Tableau
✅ Mandatory Skills
Strong expertise in Azure Databricks and Microsoft Azure
Proficiency in SQL, Python, Scala, and Apache Spark
Hands-on experience with CI/CD, DevOps, and orchestration tools such as Apache Airflow or Azure Data Factory
Strong understanding of distributed computing, performance optimization, and data security
⭐ Preferred Skills
Experience with Data Mesh, Data Fabric, or Enterprise Data Architecture
Exposure to ERP platforms such as SAP or Salesforce
Ability to drive analytics adoption and collaborate with business stakeholders
🎓 Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, or a related field
Certifications such as:
Azure Solution Architect
Azure Data Engineer
Databricks Certified Data Engineer
Databricks Certified Solutions Architect

Key Skills

Education

Bachelor's or Master's degrees