Software Engineering Lead - Data

Accountabilities:

As Software Engineering Lead – Data, you will drive the technical design and continuous improvement of the data platform, ensuring its architecture supports reliable reporting, scalable integrations, operational visibility, and future AI applications. You will collaborate across engineering and product teams to turn complex data needs into robust, maintainable solutions.

• Own and evolve the data architecture: Design and maintain the Microsoft Fabric environment, including medallion architecture with bronze, silver, and gold layers, data pipelines, and mirrored and non-mirrored databases.

• Lead Power BI development: Apply advanced Power BI expertise to develop effective reporting solutions, robust data models, and consistent reporting standards.

• Build AI-ready data foundations: Design semantic layers, data structures, and architectural patterns that support future AI use cases and enable reliable access to enterprise data.

• Develop and optimize data pipelines: Build, maintain, and improve data ingestion, transformation, and orchestration workflows using Microsoft Fabric Data Pipelines or comparable tools.

• Collaborate across technical teams: Partner with database administrators, DevOps specialists, and application engineering teams to deliver scalable, production-ready data solutions.

• Support database reliability and performance: Interpret SQL Server logs and performance indicators, identify potential bottlenecks, and contribute to the stability of highly available, 24/7 production environments.

• Implement API-based integrations: Support the design and maintenance of APIs and data exchange mechanisms that connect applications and enterprise systems.

• Establish observability practices: Monitor semantic models, pipelines, warehouses, and SQL endpoints using tools such as Azure Log Analytics and Kusto Query Language (KQL).

• Evaluate technologies and standards: Assess tools, architecture patterns, and engineering practices to improve platform maturity and support a broader data and AI strategy.

• Contribute to AI-enabled analytics: Explore emerging capabilities such as natural-language data querying, AI-assisted analytics, and data-grounding approaches.

• Support cloud platform operations: Leverage Azure services and related tooling to maintain secure, scalable, and observable data infrastructure.

• Contribute to continuous improvement: Help define technical direction, improve engineering workflows, and strengthen collaboration across a virtual-first organization.

Requirements:

The ideal candidate will bring senior-level data engineering and solution architecture experience, strong Microsoft Fabric and Power BI skills, and the ability to design cloud-based data platforms that support both current reporting needs and future AI initiatives. You should be comfortable taking ownership, working across teams, and improving systems in a collaborative, remote-first environment.

• Demonstrated senior-level experience designing data solutions, including schema design, system integration, scalability planning, and production-ready architecture.

• Hands-on expertise with Microsoft Fabric and/or Power BI, including data modeling, reporting development, and platform architecture.

• Experience designing cloud data architectures using semantic layers, medallion architecture, and modern data warehousing patterns.

• Strong SQL skills and experience designing, developing, and optimizing data pipelines.

• Working knowledge of SQL Server performance monitoring, including interpreting logs, identifying performance issues, and supporting database reliability.

• Experience with Microsoft Fabric Data Pipelines or comparable data orchestration and workflow tools.

• Experience implementing API-based data integrations and supporting reliable data exchange between systems.

• Solid understanding of the Azure ecosystem and data-related services, including App Services, virtual machines, Blob Storage, Log Analytics, and basic networking concepts.

• Familiarity with designing data architectures that can support AI-enabled applications and analytics.

• Experience with Python, Fabric notebooks, Spark, or related data-processing technologies; exposure to MLflow or model registry concepts is beneficial.

• General understanding of AI-related data patterns, including natural-language-to-data querying and the principles of grounding AI responses in trusted data sources.

• Working knowledge of PowerShell and/or Azure DevOps dashboards and pipelines.

• Strong analytical, organizational, and problem-solving skills, with the ability to evaluate technical trade-offs and recommend practical solutions.

• Excellent communication and collaboration skills, including the ability to work effectively with engineering, database, DevOps, application, and product teams.

• A proactive, self-directed approach to work, with a commitment to continuous learning, accountability, honest feedback, and high-quality outcomes.

Preferred qualifications:

• Familiarity with Power BI Embedded or similar frameworks for integrating analytics into applications.

• Hands-on experience with Azure AI Foundry, Azure OpenAI, or emerging analytics patterns such as real-time data processing, streaming, and natural-language data querying.

• Familiarity with retrieval-augmented generation (RAG), vector databases, embeddings, AI agents, or responsible AI and governance principles.

• Experience with statistical analysis, forecasting, or health-related analytics, particularly in collaboration with data scientists or product teams.

• An interest in applying modern data and AI technologies to improve public health surveillance and decision-making.

Benefits:

• Remote-first work environment and virtual-first team culture.

• Flexible paid time off (PTO).

• 401(k) retirement plan with employer matching.

• Medical, prescription, vision, and dental coverage, with multiple plan options.

• Short-term and long-term disability insurance for employees.

• Employee life insurance.

• Support for new team members setting up their home office.

• A collaborative, mission-driven environment focused on improving public health outcomes through technology.

• Opportunities to contribute to the development of modern data platforms and emerging AI-enabled analytics capabilities.