Job Description:
Role Overview
We are looking for a Data Engineer with strong experience in Azure and Apache Spark to design and build scalable, high-performance data solutions. The ideal candidate will work on modern cloud data platforms, ensuring reliable data pipelines and supporting analytics and business intelligence needs. Familiarity with Databricks and Collibra will be an added advantage.
Key Responsibilities
Design, develop, and maintain scalable data pipelines using Azure services
Build and optimize Spark-based data processing applications
Implement ETL/ELT workflows for batch and real-time data processing
Work with Azure Data Factory (ADF) or similar tools for orchestration
Store and manage data in Azure Data Lake (ADLS) or cloud storage systems
Perform data transformation, cleansing, and validation
Ensure data quality, governance, and security compliance
Collaborate with analysts, data scientists, and business stakeholders
Monitor, debug, and optimize data workflows
Required Skills & Qualifications
Technical Skills
Strong hands-on experience with Microsoft Azure (ADF, ADLS, Synapse or similar)
Solid experience in Apache Spark (PySpark preferred)
Proficiency in Python and SQL
Experience in designing data pipelines and data models
Good understanding of data warehousing concepts
Experience with version control and CI/CD pipelines (e.g., Azure DevOps)
Nice-to-Have Skills
Experience with Azure Databricks for distributed data processing
Exposure to Collibra or similar data governance/catalog tools
Knowledge of Delta Lake architecture
Familiarity with streaming technologies (Kafka, Event Hub)
Experience with BI tools such as Power BI
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