Title: Analytics Engineer Location: Atlanta, GA Duration: 10+ Months Job Description: The Analytics Engineer will contribute to our modern data estate strategy by developing scalable data solutions using Microsoft Fabric and Azure Databricks. This role will be instrumental in building resilient data pipelines, transforming raw data into curated datasets, and delivering analytics-ready models that support enterprise-level reporting and decision-making. Build and maintain ETL/ELT pipelines using Azure Databricks and Microsoft Fabric. Implement medallion architecture (Bronze, Silver, Gold layers) to support data lifecycle and quality. Develop real-time and batch ingestion processes from IES Gateway and other source systems. Ensure data quality, validation, and transformation logic is consistently applied. Use Python, Spark, and SQL in Databricks and Fabric notebooks for data transformation. Delta Lake: Implementing Delta Lake for data versioning, ACID transactions, and schema enforcement. Integration with Azure Services: Integrating Databricks with other Azure services like Azure One Lake, Azure ADLS Gen2, and Microsoft fabric. Collaborate with the Domain Owners to design dimensional and real-time data models. Create analytics-ready datasets for Power BI and other reporting tools Standardize field naming conventions and schema definitions across datasets. Apply data classification and tagging based on DECAL's data governance framework. Implement row-level security, data masking, and audit logging as per compliance requirements. Support integration with Microsoft Purview for lineage and metadata management. Dimensional modeling Real-time data modeling patterns Partner with BI developers to ensure data models are optimized for Power BI. Provide curated datasets that align with reporting requirements and business logic. Create BI dashboards and train users. Support CI/CD pipelines for data workflows using Azure DevOps. Assist in monitoring, logging, and performance tuning of data jobs and clusters. Skills: 3+ years of experience in data engineering or analytics engineering roles. Advanced SQL: Proficiency in advanced SQL techniques for data transformation, querying, and optimization Azure Databricks (Spark, Delta Lake) Microsoft Fabric (Dataflows, Pipelines, OneLake) SQL and Python (Pandas, PySpark)