Posted on: 11/06/2026



Job Description :
- Design, develop, and maintain scalable data pipelines using Microsoft Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake.
- Build and optimize ETL/ELT workflows for structured and unstructured data processing across multiple business systems.
- Develop high-performance data transformation logic using SQL, Python, and PySpark to support analytics and reporting requirements.
- Implement and manage large-scale data ingestion frameworks from various sources including APIs, databases, flat files, and cloud platforms.
- Work extensively with relational databases (RDBMS) to design schemas, write optimized queries, and improve database performance.
- Create scalable and reusable data models for enterprise data warehousing and business intelligence solutions.
- Monitor, troubleshoot, and enhance existing Azure-based data engineering solutions to ensure reliability, scalability, and performance.
- Collaborate with business stakeholders, data analysts, architects, and cross-functional teams to gather requirements and deliver data-driven solutions.
- Ensure data quality, governance, security, and compliance standards are maintained across all data platforms.
- Automate data workflows and deployment processes using CI/CD and DevOps best practices within Azure environments.
- Optimize PySpark jobs and distributed processing workloads for handling large datasets efficiently.
- Support cloud migration and modernization initiatives involving on-premise to Azure data platform transitions.
- Prepare technical documentation, data flow diagrams, and operational runbooks for developed solutions.
- Mentor junior engineers and contribute to best practices in data engineering and cloud data architecture.
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Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1643799