Data Analytics Engineer 4

The Data Engineer is responsible for designing, building, and supporting scalable data platforms, data products, application integrations, and analytics solutions that enable business decision-making across Power Delivery. This role develops and maintains enterprise data pipelines, integrates operational systems with cloud-based lakehouse platforms, and supports both low-code and pro-code application development using Microsoft Power Platform, OutSystems, and Databricks.

The successful candidate partners with business stakeholders, data analysts, application developers, and technology teams to deliver trusted, governed, and reusable data assets., * Data Engineering & Integration

• Design, build, and support enterprise data pipelines using ETL and ELT methodologies.
• Develop scalable ingestion frameworks for structured, semi-structured, and streaming data.
• Build and maintain Databricks notebooks, workflows, and data pipelines.

• Ingest data from source systems using: o Azure Data Factory o Kafka o CDC technologies o APIs o Files and database sources

• Implement data quality checks, monitoring, and exception handling.
• Support Bronze, Silver, and Gold (Medallion) data architectures within the Databricks Lakehouse.
• Databricks Development
• Design and maintain Delta Lake tables and data products.

• Develop solutions using: o Databricks o PySpark o Spark SQL o Python o SQL

• Optimize lakehouse performance, scalability, and cost management.
• Support data sharing, governance, and catalog management using Unity Catalog.
• Application Development

• Build and enhance business applications using: o Microsoft Power Apps o Power Automate o Microsoft Power Platform o OutSystems

• Develop integrations between Databricks and business applications.
• Partner with users to automate workflows and operational processes.
• Data Governance & DevOps
• Follow Company governance and security standards.
• Implement CI/CD practices using GitHub and Azure DevOps.
• Maintain documentation, data lineage, and metadata for enterprise data assets.
• Participate in architecture reviews and solution design activities., * Data Engineering
• ETL / ELT design and development
• Data ingestion frameworks
• Data pipeline orchestration
• Data warehousing concepts
• Data Lake and Lakehouse architectures
• Medallion architecture
• Databricks
• Databricks
• Databricks Workflows
• PySpark
• Spark SQL
• Delta Lake
• Unity Catalog
• Data Products
• Cloud & Integration
• Azure Data Factory
• APIs
• Kafka
• CDC technologies
• SQL Server
• Development
• Python
• SQL
• GitHub
• Azure DevOps
• Business Applications
• Microsoft Power Apps
• Power Automate
• Microsoft Power Platform
• OutSystems, * The position is listed as hybrid because team members come into the office as needed for meetings with business partners. Currently, we do not have sufficient office space for all workers to be onsite Monday through Thursday from 8:00 AM to 5:00 PM.

• Bachelor’s degree in one of the following:
• Computer Science
• Information Systems
• Data Analytics
• Engineering
• Related technical discipline

Experience

• 3-7 years of experience in data engineering, analytics engineering, or software development.
• Experience building enterprise data pipelines and integrations.
• Experience working with cloud-based data platforms., * Utility industry experience
• Power Delivery domain knowledge
• Experience supporting Transmission or Distribution Analytics
• Real-time data streaming experience
• Knowledge of AI/ML enablement on Databricks
• Experience with Power BI integration and DirectQuery architectures

Why Choose The E Group? We are an award winning firm recognized for having an outstanding reputation with our clients and employees. All contractors are eligible for full group health and dental benefits, 401K with matching, and various insurances. Generous living expenses are given to help those who relocate or have duplicate housing.