Mid-Level DATA ENGINEER: Microsoft Power Platform & AI Copilot Studio (HYBRID)

State Farm•Dunwoody, GA

3d•Hybrid

About The Position

State Farm is building the next generation of AI-powered business solutions, and data is at the center of that transformation. The Power Platform team is looking for a Data Engineer who is passionate about building modern, scalable data solutions that enable automation, analytics, AI-powered experiences, and intelligent applications across the enterprise. Our team works closely with Microsoft engineering and product teams to evaluate and enable emerging technologies. In this role, you'll help design and deliver scalable, secure, and governed data solutions that support Microsoft Power Platform, AI, Microsoft Fabric, Dataverse, and other cloud technologies. This is an opportunity to help shape the data foundation supporting modern application development, automation, analytics, and AI at enterprise scale.

Requirements

3+ years of professional data engineering experience, including designing and building production data pipelines, integrations, or data solutions.
3+ years of experience with SQL, including querying, data transformation, and data modeling.
2+ years of experience using Python for data engineering, automation, data transformation, or pipeline development.
2+ years of experience with modern cloud data technologies, such as Microsoft Fabric, Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Snowflake, or comparable cloud data platforms.
Experience applying modern DataOps and software engineering practices, including version control, automated testing, CI/CD, and deployment.
Experience working with structured, semi-structured, and unstructured data.
Strong analytical and problem-solving skills with the ability to independently investigate and solve technical problems.
Strong written and verbal communication skills and the ability to collaborate across technical and business teams.

Nice To Haves

Microsoft Power Platform
Databricks
Microsoft Dataverse
Microsoft Fabric and OneLake
Microsoft Graph
Microsoft Foundry or Azure OpenAI
Data engineering supporting AI or generative AI applications
Lakehouse architecture
Power BI semantic models and enterprise analytics
REST APIs and event-driven architectures
Microsoft Azure certifications

Responsibilities

Design, build, and maintain scalable data pipelines, integrations, and data solutions.
Develop reusable data products that support AI, Power Platform, analytics, reporting, and enterprise automation.
Engineer data solutions that support AI and generative AI use cases, including the preparation, integration, and delivery of trusted enterprise data for intelligent applications.
Partner with software engineers, architects, citizen developers, and business partners to design and deliver trusted data solutions.
Transform, cleanse, profile, and validate structured, semi-structured, and unstructured data from enterprise and external sources.
Apply DataOps practices including source control, automation, monitoring, testing, continuous integration and continuous delivery (CI/CD), and deployment.
Design solutions that integrate data from application programming interfaces (APIs), databases, software-as-a-service (SaaS) platforms, and enterprise systems.
Support secure, governed, and compliant data solutions aligned with enterprise standards.
Contribute to modern cloud data architecture and evaluate emerging technologies that improve engineering productivity and platform capabilities.
Help establish reusable patterns and engineering best practices for enterprise data solutions.