Analytics Engineer job
Role details
Job location
Tech stack
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.
Work Location & Attendance Requirements: &bull Must be physically located in Georgia &bull On-site: Tuesday to Thursday, per manager's discretion &bull Mandatory in-person meetings:
o All Hands
o Enterprise Applications
o On-site meetings
o DECAL All Staff &bull Work arrangements subject to management's decision, Data Engineering & Pipeline Development &bull Build and maintain ETL/ELT pipelines using Azure Databricks and Microsoft Fabric. &bull Implement medallion architecture (Bronze, Silver, Gold layers) to support data lifecycle and quality. &bull Develop real-time and batch ingestion processes from IES Gateway and other source systems. &bull Ensure data quality, validation, and transformation logic is consistently applied. &bull Use Python, Spark, and SQL in Databricks and Fabric notebooks for data transformation. &bull Delta Lake: Implementing Delta Lake for data versioning, ACID transactions, and schema enforcement. &bull Integration with Azure Services: Integrating Databricks with other Azure services like Azure One Lake, Azure ADLS Gen2, and Microsoft fabric.
Data Modeling & Curation &bull Collaborate with the Domain Owners to design dimensional and real-time data models. &bull Create analytics-ready datasets for Power BI and other reporting tools. &bull Standardize field naming conventions and schema definitions across datasets.
Data Governance & Security &bull Apply data classification and tagging based on DECAL's data governance framework. &bull Implement row-level security, data masking, and audit logging as per compliance requirements. &bull Support integration with Microsoft Purview for lineage and metadata management.
Data Modeling: &bull Dimensional modeling &bull Real-time data modeling patterns
Reporting & Visualization Support &bull Partner with BI developers to ensure data models are optimized for Power BI. &bull Provide curated datasets that align with reporting requirements and business logic. &bull Create BI dashboards and train users.
DevOps & Automation &bull Support CI/CD pipelines for data workflows using Azure DevOps. &bull Assist in monitoring, logging, and performance tuning of data jobs and clusters.
Requirements
&bull Bachelor's degree in computer science, Data Engineering, or related field. &bull 3+ years of experience in data engineering or analytics engineering roles. &bull Advanced SQL: Proficiency in advanced SQL techniques for data transformation, querying, and optimization. &bull Hands-on experience with:
o Azure Databricks (Spark, Delta Lake)
o Microsoft Fabric (Dataflows, Pipelines, OneLake)
o SQL and Python (Pandas, PySpark)
o SQL Server 2019+ &bull Familiarity with data modeling, data governance, and data security best practices. &bull Strong understanding of ETL/ELT processes, data quality, and schema design.
Preferred Skills: &bull Experience with Power BI datasets and semantic modeling. &bull Knowledge of Microsoft Purview, Unity Catalog, or similar governance tools. &bull Exposure to real-time data processing and streaming architectures. &bull Knowledge of federal/state compliance requirements for data handling &bull Familiarity with Azure DevOps, Terraform, or CI/CD for data pipelines.
Certifications (preferred): &bull Microsoft Fabric Analytics Engineer.
Soft Skills: &bull Strong analytical and problem-solving abilities. &bull Excellent communication skills for technical and non-technical audiences. &bull Experience working with government stakeholders.
