Design, build, and maintain Azure-based data pipelines and data models using Synapse, Spark, SQL and ADLS. Implement ETL/ELT, ensure data quality, optimize performance, support deployment/monitoring, and collaborate with analysts, scientists, and stakeholders.
Key Responsibilities
- Design, build, and maintain data pipelines using Azure services
- Develop and optimize solutions using Azure Synapse Analytics (pipelines, Spark, SQL pools)
- Implement ETL/ELT processes for ingesting and transforming data from multiple sources
- Design and manage data models to support reporting and analytics
- Work with structured and unstructured datasets in a data lake environment
- Ensure data quality, integrity, and consistency across pipelines
- Optimize performance of queries, pipelines, and storage
- Collaborate with data analysts, data scientists, and business stakeholders
- Support deployment, testing, and monitoring of data solutions
- Maintain documentation for data processes and architectures
Required Skills & Experience
- Strong hands-on experience with Microsoft Azure data services
- Proven experience with Azure Synapse Analytics (pipelines, Spark, SQL)
- Proficiency in SQL and Python
- Experience with data warehousing concepts and dimensional modeling
- Experience with ETL/ELT design and implementation
- Familiarity with Azure Data Lake Storage (ADLS)
- Understanding of distributed data processing (e.g., Spark)
- Experience with version control and CI/CD practices (Azure DevOps preferred)
Soft Skills
- Strong analytical and problem-solving abilities
- Good communication and stakeholder interaction skills
- Ability to work independently and within a team
- Attention to detail and focus on quality
Preferred Qualifications
- 6+ years of experience in Data Engineering.
- Experience with Delta Lake or similar technologies
- Exposure to Azure Data Factory
- Knowledge of performance tuning and query optimization
- Understanding of data governance and security best practices in Azure
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