Job Description
Technical Specifications:
3+ years of experience in Data Engineering, Data Platform Development, or related fields. Strong hands-on experience with Azure Data Platform services and modern cloud-based data architectures.
Mandatory experience with: Microsoft Fabric, Azure Databricks, Snowflake, SQL, PySpark Strong understanding of cloud-based data warehousing and lakehouse concepts, including Fabric, Snowflake, and Databricks.
Experience in designing, building, and maintaining scalable data pipelines and ETL/ELT frameworks. Hands-on experience with ETL/ELT tools such as Azure Data Factory, Microsoft Fabric Data Pipelines, DBT, Synapse Analytics, or similar technologies.
Experience in implementing data governance, data quality, security, and compliance standards across enterprise data platforms. Knowledge of CI/CD practices, version control, and DevOps methodologies.
Required Skillset: Mandatory Skills: Microsoft Fabric, Azure Databricks, Snowflake, DBT, SQL, PySpark, Azure Data Platform Services, ETL/ELT development using Azure Data Factory, Fabric Data Pipelines, Synapse, or DBT
Preferred Skills: AWS Data Engineering ecosystem, AWS Glue, Redshift, Power, BI/Tableau, Looker, Docker, Kubernetes, Git and CI/CD tools.
Cloud Experience: Azure (Mandatory), AWS (Secondary/Preferred), GCP (Good to Have)
Data Warehousing: Snowflake (Mandatory), Azure Fabric Warehouse, Azure Databricks, Azure SQL, Redshift (Good to Have).
Certifications (Good to Have): Microsoft Azure Data Engineer Associate Microsoft Fabric Analytics Engineer Associate Databricks Certifications SnowPro Certifications’
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