You will work closely with clients, architects, and cross-functional teams to deliver robust data solutions that support analytics, reporting, and advanced data processing.
Design and implement end-to-end data engineering solutions on Microsoft Azure.
Develop and maintain data pipelines using Azure Data Factory (ADF).
Build scalable data processing frameworks using Azure Databricks (PySpark/Scala).
Architect and manage data lakes using Azure Data Lake Storage (ADLS Gen2).
Develop data warehousing and analytics solutions using Azure Synapse Analytics.
Work with HDInsight for big data workloads (Hive, Spark, Kafka, etc.) where applicable.
Optimize data workflows for performance, scalability, and cost-efficiency.
Implement data governance, security, and compliance best practices.
Collaborate with stakeholders to gather requirements and translate them into technical solutions.
Provide technical leadership and mentor junior team members.
Troubleshoot production issues and ensure high availability of data systems.
Required Skills & Qualifications
Core Technical Skills
Robust experience with
Azure Data Factory (ADF)
Azure Databricks (PySpark, Spark SQL)
Azure Data Lake Storage (ADLS Gen2)
Azure Synapse Analytics
HDInsight (Spark/Hadoop ecosystem)
Proficiency in Python and/or Scala
Strong SQL and data modeling skills (star/snowflake schema)
Experience with ETL/ELT design patterns
Knowledge of distributed data processing frameworks
Azure & Data Expertise
Hands-on experience with Azure-native data services
Understanding of data lake, lakehouse, and data warehouse architectures