Senior Data Engineer / DevOps Consultant

Role overview

Svitla Systems Inc. is looking for a Senior Data Engineer / DevOps Consultant for a part-time position in the USA. Our client is a technology company that develops software solutions for public sector organizations. Its products help government agencies and educational institutions streamline essential operations, manage data and services. The company focuses on modernizing complex administrative processes through integrated, secure, and scalable digital solutions.

In this role, you will work directly alongside the client's Microsoft Fabric data engineering team to mature its software engineering, DevOps, and delivery practices.

The team currently builds and maintains data solutions in Microsoft Fabric using a bronze/silver/gold architecture, including data pipelines, ETL/PySpark, dimensional models, and semantic models. The primary objective of this engagement is not simply to build data solutions for the team, but to help establish repeatable engineering practices, processes, automation, and tooling needed to operate a modern data engineering organization.

The consultant should combine strong Microsoft Fabric and data engineering experience with practical experience implementing DevOps and software engineering practices in data environments. This person must be comfortable both working hands-on with engineers and assessing current practices, identifying gaps, defining a practical future state, and helping the team implement it.

This is a part-time consulting engagement, primarily remote with periodic onsite working sessions in the Dallas, Texas area.

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.

• Will be a plus

• 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.

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.

• We offer

• US and EU projects based on advanced technologies.

• Competitive compensation based on skills and experience.

• Flexibility in workspace, either remote or our welcoming office.

• Bonuses for article writing, public talks, and other activities.

• Free tech webinars and meetups organized by Svitla.

• Regular corporate online activities.

• Awesome team, friendly and supportive community!

• Why join Svitla

• Svitla Systems is a global digital solutions company headquartered in the U.S. and operating across the Americas, Europe, Asia, and APAC. Since 2003, we have served a wide range of clients - from innovative start-ups to Fortune 500 companies. Our success is built on partnership. By integrating seamlessly with clients' teams, we create lasting collaborations that drive real results. We are strong advocates of workplace flexibility, remote culture, individual approach to professional and personal growth.

• Our global mission is to build a business that contributes to wellbeing of our partners, personnel, and their families, improves our communities, and makes a lasting difference in the world. Together, we are coding a brighter tomorrow - and living it.

• Join us!