Design, develop, and maintain scalable data pipelines and analytics-ready datasets using the Microsoft Azure data ecosystem. Integrate diverse data sources, implement ETL/ELT processes, and collaborate with stakeholders, architects, and product teams to deliver reliable, production-grade data solutions for analytics and transformation initiatives.
This is a remote position.
We are seeking an experienced Senior Data Engineer to design, develop, and maintain scalable data solutions for a large-scale digital transformation initiative. The successful candidate will work closely with business stakeholders, product owners, data architects, and technical teams to build reliable data pipelines, integrate diverse data sources, and deliver trusted, analytics-ready datasets. The role will focus heavily on the Microsoft Azure data ecosystem, including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage Gen2, Python, SQL, and Delta Lake.
Requirements
- Minimum 5 years of hands-on experience with Python and SQL for data engineering.
- Minimum 3 years of experience with Azure services, including Azure Storage, Azure SQL, Azure Synapse, and Azure networking.
- Minimum 3 years of hands-on experience with Azure Databricks and Delta Lake.
- Minimum 3 years of experience designing data solutions and developing trusted, analytics-ready datasets.
- Minimum 4 years of experience using version control systems such as Git.
- Minimum 1 year of experience using AI tools for code generation, data analysis, automation, optimization, or related data engineering activities.
- Strong understanding of data engineering principles, ETL/ELT processes, data integration, and data pipelines.
- Strong SQL development and data transformation skills.
- Experience working with cloud-based data platforms and modern data architectures.
- Strong problem-solving, analytical, and communication skills.
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