Overview
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.
Responsibilities
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
Qualifications
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 Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience.
Preferred Qualifications
- Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 6+ years experience in business analytics, data science, software development, data modeling, or data engineering OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 8+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience.
- 2+ years experience with data governance, data compliance and/or data security.
- Proficiency in SQL and Python for data processing, pipeline development, and analysis
- Hands-on experience building and maintaining data pipelines on cloud platforms (Azure, AWS, GCP, or similar)
- Demonstrated ability to understand and document complex multi-system technology environments end to end
- Experience managing or contributing to proof-of-concept or pilot evaluations of new technologies
- Familiarity with API design, integration patterns (REST, event-driven), and middleware
- Exposure to AI/ML tools or agentic workflows for document processing, search, or automation
- Experience supporting legal, compliance, or business operations teams in a technology capacity
- Understanding of data governance, privacy requirements, and access control in regulated or sensitive environments
- Project management skills or experience with agile methodologies
Data Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about **requesting accommodations.**