SSE Data Engineer
CGI (company site, opens in a new tab)6–8 yrsBengaluruOn-siteDirect career pageEst. 18–30 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and maintain scalable Azure data engineering solutions, including ETL/ELT pipelines and distributed data processing using Spark and PySpark.
- Implement and manage data lake and data warehouse architectures using Azure Data Lake Storage Gen2, Azure Synapse Analytics, and dimensional modeling.
- Optimize performance and reliability of large-scale data pipelines; implement batch and real-time processing with Azure Event Hubs and Azure Functions, ensuring data governance and security.
Minimum Requirements
- 6–8 years of hands-on experience in Data Engineering and Data Warehousing.
- Strong expertise with Azure data platform services including ADLS Gen2, Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Event Hubs, and Azure Functions.
- Proficiency in SQL (with query optimization and tuning), Python, PySpark, Apache Spark, and experience building cloud-based ETL/ELT pipelines.
- Experience with pipeline orchestration tools (Azure Data Factory, Apache Airflow, Databricks Workflows, or Microsoft Fabric pipelines) and DevOps practices (CI/CD, Git, Infrastructure as Code tools like Terraform or Bicep).
Ideal Candidate Profile
- Experienced engineer skilled in designing end-to-end cloud-native data solutions on Microsoft Azure with strong distributed data processing expertise.
- Familiar with modern lakehouse technologies and formats (Delta Lake, Apache Iceberg, Apache Hudi) and implementing data governance and security in enterprise-scale environments.
- Able to collaborate effectively across architects, business stakeholders, and teams to deliver reliable, high-quality data solutions while troubleshooting and optimizing complex pipelines.