Sr Data Engineer

We are looking for a full stack Azure Data Engineer to serve as the primary technical partner for our Legal Business Operations team. This is a hands-on role focused on deeply understanding the end-to-end technology stack that supports legal operations and provides technical guidance and support on platform modernization using AI.

You will be the person who knows how all the pieces connect: how data flows between systems, where integrations are fragile, what the downstream impact of a schema change is, and how to evaluate whether a new tool or approach is worth adopting. You will manage proof-of-concept evaluations, support production operations, and act as the bridge between legal operations stakeholders and engineering resources.

This is not a pure backend engineering role. It requires someone who is equally comfortable digging into data pipelines, troubleshooting a dashboard, and walking a non-technical stakeholder through the implications of a platform migration.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Technology Stack Ownership & Operations

• Develop and maintain a deep, end-to-end understanding of the legal business operations technology stack — including case management platforms, document management systems, workflow automation tools, dashboards, and reporting infrastructure
• Serve as the go-to technical expert for how systems are configured, how data flows between them, and how changes in one system affect others downstream
• Monitor system health, data quality, and pipeline reliability; proactively identify and resolve issues before they impact operations
• Own technical documentation:  system architecture diagrams, data flow maps, integration specifications, and operational runbooks
• Manage and coordinate system updates, configuration changes, and data migrations with minimal disruption to end users

Proof-of-Concept Management & Evaluation

• Lead proof-of-concept evaluations for new tools, platforms, and technical approaches, scoping and requirements gathering through hands-on prototyping and stakeholder demo
• Define clear success criteria for each proof of concept; collect and analyze data to produce objective recommendations on whether to adopt, iterate, or abandon.
• Manage the transition from successful proof of concept to production deployment, including integration planning, data migration, testing, and rollout.
• Stay current with emerging technologies relevant to legal operations, including low-code platforms, AI-assisted document review, workflow automation, and data analytics tools.
• Evaluate vendor offerings and third-party solutions against build-vs-buy criteria, total cost of ownership, and long-term maintainability.

Data Engineering & Pipeline Development

• Design, build, and maintain data pipelines that ingest, transform, and deliver data across the legal operations technology stack
• Build and optimize data models and schemas to support reporting, analytics, and operational workflows
• Implement data quality checks, validation rules, and monitoring to ensure accuracy and completeness of operational data
• Develop and maintain integrations between systems (APIs, file-based transfers, event-driven workflows) to keep data synchronized and current
• Support ad hoc data requests, extracts, and analysis for legal operations stakeholders

Stakeholder Partnership & Communication

• Act as the primary technical liaison between the legal business operations team and engineering, data science, and platform teams
• Translate business requirements into technical specifications and vice versa — making complex technical concepts accessible to non-technical stakeholders
• Participate in planning and prioritization discussions, providing technical feasibility assessments and level-of-effort estimates
• Coordinate with external vendors and consulting partners on technical deliverables, data access, and integration requirements
• Proactively surface risks, dependencies, and technical debt to stakeholders with clear recommendations

Required Qualifications

• Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years experience in business analytics, data science, software development, data modeling, or data engineering OR Bachelor's Degree in Computer Science, Math, Software