Data Engineer (Azure)

About the role

We are looking for an experienced Data Engineer to design, build and maintain metadata‑driven ELT/ETL frameworks on Azure. The role focuses on creating scalable data pipelines, data lakes and data warehouse solutions that support both structured and unstructured data.

Key responsibilities

• Create and maintain optimal, scalable data pipeline architecture.
• Assemble large, complex data sets to meet functional and non‑functional business requirements.
• Automate manual processes, optimize data delivery and redesign infrastructure for greater scalability.
• Build infrastructure for extraction, transformation and loading from diverse data sources.
• Design, model, implement and operate large structured and unstructured data sets.
• Evaluate and implement efficient distributed storage and query techniques.
• Design and implement monitoring of data services platforms.
• Develop Data Lakes and Data Warehouse solutions on Azure.
• Maintain technical documentation and operational procedures.

Required profile

• 8+ years of hands‑on ETL development and data pipeline design.
• Production experience building metadata‑driven ELT/ETL frameworks.
• Strong background with Azure data services (ADLS Gen2, Databricks, Data Factory, Synapse Analytics, Stream Analytics, Event Hubs, Data Explorer, Purview).
• Experience with relational and NoSQL databases, especially Azure SQL Database and Azure Data Lake.
• Proficiency in programming and scripting languages such as Python, Scala, Java, Bash, Azure CLI and PowerShell.
• Solid understanding of CI/CD practices using Azure DevOps.
• Experience with MS SSIS, Informatica IDMC and business requirements analysis.
• Knowledge of big‑data tools (Hadoop, Spark, Kafka, Storm, Hive, HBase) is a plus.

Required skills

• Azure ADLS Gen2
• Databricks
• Azure Data Factory
• Azure Synapse Analytics
• Azure Stream Analytics
• Azure Event Hubs
• Azure Data Explorer
• Azure SQL Database
• Azure Data Lake
• Azure Purview
• Python
• Scala
• Java
• Bash
• Azure CLI
• PowerShell
• Azure DevOps
• MS SSIS
• Informatica IDMC
• Hadoop
• Spark
• Kafka
• Storm
• Hive
• HBase
• CI/CD