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We are seeking a Data Engineer with strong experience in Microsoft Azure and Databricks to help design, build, and maintain modern cloud-based data solutions. This individual will play a key role in developing scalable data pipelines, optimizing data architectures, and enabling business intelligence and analytics initiatives across the organization. This is an excellent opportunity for someone passionate about cloud technologies, big data, and transforming raw data into actionable insights.
Job Responsibility
Design, develop, and maintain scalable data pipelines in Azure and Databricks
Build and optimize ETL/ELT processes for structured and unstructured data
Develop and support data lake, data warehouse, and analytics solutions
Integrate data from multiple internal and external sources
Collaborate with business analysts, data scientists, and stakeholders to understand data requirements
Ensure data quality, integrity, security, and governance standards are met
Monitor and troubleshoot data workflows and performance issues
Create and maintain technical documentation and data models
Support reporting and analytics initiatives by delivering reliable datasets
Requirements
5+ years of Data Engineering experience
Hands-on experience with Azure Databricks
Experience with Azure services such as: Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Azure Synapse Analytics, Azure SQL Database
Strong SQL development skills
Experience with Python, PySpark, or Spark
Experience building and maintaining ETL/ELT pipelines
Understanding of data warehousing concepts and dimensional modeling
Experience working with large datasets in cloud environments
Nice to have
Experience with Delta Lake and Lakehouse architectures
Knowledge of CI/CD pipelines and DevOps practices
Experience with Power BI or other reporting tools
Familiarity with data governance and security best practices
Experience supporting machine learning or AI data initiatives
Bachelor's degree in Computer Science, Information Systems, or a related field