Senior Data Engineer / DevOps Consultant

Svitla Systems, Inc. is seeking a Senior Data Engineer / DevOps Consultant for a part-time consulting engagement supporting a technology company that develops software solutions for public sector organizations. The role will work hands-on with a Microsoft Fabric data engineering team to mature data engineering, DevOps, software engineering, delivery, automation, and Agile practices while providing guidance and knowledge transfer.

Responsibilities:

• Data Engineering & Microsoft Fabric: Work credibly and hands-on within a Microsoft Fabric data engineering environment. Understand and support bronze/silver/gold medallion architectures and the engineering lifecycle associated with each layer. Work with data pipelines, ETL/ELT, PySpark processes, dimensional models, fact and dimension tables, and semantic models. Understand dependencies across shared schemas, common dimensions, fact tables, and related data assets
• DevOps & Software Engineering Practices: Assess the team’s current development and delivery practices and document the current state. Define a practical future-state operating model and identify gaps between current and desired practices. Help establish repeatable software engineering and DevOps practices appropriate to a data engineering team. Implement or improve GitHub-based source control, branching, pull-request, check-in/check-out, versioning, and labeling practices. Improve CI/CD and release-management practices for Microsoft Fabric. Establish repeatable processes for promoting Fabric artifacts across development, test, and production environments. Establish and test appropriate deployment and rollback practices. Help incorporate user acceptance testing and other quality controls into the team’s development lifecycle
• Agile & Engineering Workflow: Help structure engineering work using Jira, including appropriate use of initiatives/epics, stories, tasks, and work associated with bronze, silver, and gold development. Help the team adopt lightweight Agile practices appropriate to a small data engineering organization, such as Kanban or Scrumban. Improve visibility into work in progress, priorities, dependencies, and engineering capacity. Help establish an iterative roadmap for maturing engineering practices over time rather than attempting to change everything at once
• Automation & AI-Assisted Development: Identify repetitive administrative and engineering activities that can be automated. Help connect development workflows across tools such as GitHub, Jira, Confluence, and Microsoft Teams where appropriate. Apply deterministic automation for repeatable production processes. Work with AI-assisted development tools where they can improve developer productivity, context gathering, documentation, workflow management, or other engineering activities. Help the team understand where AI-assisted tooling adds value and where traditional automation is more appropriate
• Enablement & Knowledge Transfer: Work directly alongside the client’s engineers on real production work rather than providing classroom-only training. Translate current-state and gap findings into practical recommendations and an incremental improvement plan. Help engineers implement new practices and tooling so the team can operate them independently. Participate in periodic onsite working sessions as needed

Requirements:

• Senior-level data engineering experience
• Strong hands-on experience with Microsoft Fabric
• Strong hands-on data engineering background in modern cloud data environments
• Strong practical experience with Microsoft Azure
• Experience working with data pipelines and ETL/ELT workflows
• Experience with bronze/silver/gold or comparable medallion data architectures
• Experience with dimensional modeling, including fact tables, dimension tables, common/conformed dimensions, and star-schema concepts
• Strong Git/GitHub experience, including source control, pull requests, branching/versioning, and deployment workflows
• Hands-on experience with DevOps and CI/CD practices
• Experience with deployment, environment promotion, and rollback practices
• Experience working across development, test, and production environments
• Experience implementing or improving engineering processes and development workflows
• Experience working with Agile engineering practices
• Ability to work hands-on with an existing engineering team while providing guidance and knowledge transfer
• Ability to assess current engineering practices, identify gaps, recommend a future state, and help implement practical improvements
• Experience specifically implementing CI/CD and deployment practices within Microsoft Fabric
• PySpark experience
• Python experience
• Experience with Microsoft Fabric semantic models
• Power BI experience
• Experience with GitHub Actions
• Experience with data quality, data lineage, governance, schema management, and dependency management
• Experience working with Jira and Confluence
• Experience working with Microsoft Teams as part of engineering workflows
• Experience with AI-assisted development tools such as Claude, GitHub Copilot, or similar tools
• Experience using AI agents, MCP integrations, or similar approaches to automate developer workflows
• Experience helping data engineering teams adopt mature software engineering and DevOps practices
• Experience with production support or database operational processes
• Experience working with automation and AI-assisted development in engineering environments