Data Engineer Deb

Job Description:

We are seeking a hands-on Data Engineer or Associate Data Engineer with strong programming skills in Python and SQL and practical experience building scalable data ingestion transformation and quality pipelines using Azure ecosystem.

This role will focus on building scalable ingestion pipelines into the Bronze layer developing Silver and Gold layer patterns with strong focus on data quality and enabling governed semantic models through Microsoft Fabric for analytics and reporting.

Technical Skills: Python SQL PySpark Pandas Azure Databricks Azure Data Factory Snowflake Star Schema Dimensional Modeling and Microsoft Fabric.

Key Responsibilities

Implement medallion lakehouse architecture patterns across Bronze Silver and Gold layers.

Build and maintain ingestion pipelines that bring structured semi-structured data files API sources into the Bronze layer of the lakehouse.

Develop Silver layer patterns focused on data cleaning standardization deduplication validation and business-rule application.

Develop Gold layer datasets that are curated analytics-ready and suitable for enterprise reporting and semantic model consumption.

Build reliable data pipelines using Azure Databricks SQL and Python.

Design and support orchestration workflows using Azure Data Factory Implement data quality checks reconciliation logic exception handling and monitoring across pipelines.

Support enterprise data warehouse design including dimensional modeling star schemas fact tables and dimension tables.

Prepare curated datasets that support semantic models governed reporting dashboards and business intelligence use cases.

Enable semantic layers and semantic models through Microsoft Fabric including Fabric Lakehouse Fabric Warehouse OneLake and Power BI semantic model integration.

Optimize data pipelines transformations models and processing jobs for performance scalability and maintainability.

Collaborate with data analysts BI developers business stakeholders and platform teams to translate requirements into trusted reusable data products.

Communicate technical concepts clearly to both technical and non-technical stakeholders.

Required Skills and Experience

Data Engineer 3-5 years of industry experience in data engineering analytics engineering and enterprise data platforms

Strong hands-on experience with SQL and Python for data pipeline development transformation validation and performance optimization.

Experience building ingestion pipelines into a lakehouse cloud data platform or enterprise data warehouse.

Experience designing and implementing Bronze Silver and Gold layers in a medallion lakehouse architecture.

Hands-on experience with Azure Databricks and distributed data processing.

Experience with Snowflake including data loading transformation performance tuning and integration with cloud platforms.

Experience implementing data cleaning standardization deduplication validation reconciliation and data quality rules.

Working experience with enterprise data warehouses dimensional modeling star schemas fact tables and dimension tables.

Hands on experience with Microsoft Fabric a plus Experience creating curated datasets for reporting analytics dashboards and semantic model consumption.

Understanding of data governance metadata management lineage monitoring and production support best practices.

Ability to own specific data domains act as a subject matter expert and guide implementation patterns.

Preferred Qualifications

Azure Microsoft Fabric Databricks or Snowflake certification preferred.

Experience with Delta Lake Unity Catalog OneLake or similar lakehouse governance technologies.

Experience implementing reusable ingestion Silver transformation and Gold curation patterns.

Experience supporting Power BI or Microsoft Fabric semantic model development.

Experience building production-grade data pipelines for enterprise analytics reporting or data platform modernization.