Principal Data Engineer

Role Description

This is a duration based role that will last 2 years. The Principal Data Engineer owns product engineering and architectural decisions, serving as both the technical visionary and hands-on leader responsible for solution delivery. This role partners closely with Product Owners, Product Group Engineers, Lead Engineers, architects, and cross-functional product squads to solve complex engineering challenges, define scalable technical solutions, and ensure alignment with enterprise technology strategy.

The role is accountable for product technical architecture, engineering standards, technology roadmaps, and the successful delivery of scalable, secure, and governed data and AI solutions. The ideal candidate brings 10+ years of progressive experience in enterprise data engineering, architecture, analytics, and AI, with deep expertise in:

• Azure
• Microsoft Fabric
• Databricks
• Power BI
• Data Mesh
• Data Federation
• Data Modeling
• Data Governance
• Enterprise Data Management
• Generative AI
• Agentic AI platforms

Responsibilities

• Lead the end-to-end data integration strategy for the Butterfly program, ensuring seamless data movement across CRM, ERP, MDM, CDP, analytics, and downstream platforms.
• Own integration architecture decisions, standards, and patterns across batch, real-time, API-based, event-driven, and file-based integrations.
• Partner with business, product, and application teams to define data exchange requirements and align with enterprise data standards.
• Drive the design, development, testing, and deployment of scalable integration solutions supporting global releases and country rollouts.
• Establish and govern integration design reviews, technical specifications, mapping documents, and interface contracts.
• Coordinate cross-functional teams to manage integration dependencies, risks, and release readiness.
• Serve as the primary technical lead for application onboarding, source-to-target mapping, integration assessments, and data flow design.
• Ensure integration solutions meet performance, reliability, scalability, security, and compliance requirements.

Technical Scope & Expectations (Data Engineering Focus)

• Design and implement enterprise integration solutions using APIs, ETL/ELT pipelines, messaging frameworks, event-driven architectures, and cloud-native integration patterns.
• Lead source system onboarding and integration of commercial, customer, product, consent, and transactional data into Butterfly data products.
• Establish reusable integration frameworks, canonical data models, and standardized mapping approaches to accelerate delivery and reduce complexity.
• Embed data quality controls, reconciliation processes, exception handling, and monitoring capabilities into all integration solutions.
• Collaborate with MDM, Data Product, Analytics, Experience, and Application teams to support a unified enterprise data ecosystem.
• Define integration observability standards, including logging, alerting, monitoring, SLA management, and operational support processes.
• Drive API-first integration strategies and support the governance and lifecycle management of enterprise APIs and data services.
• Lead migration and modernization efforts from legacy integrations to cloud-native architectures leveraging Azure, Databricks, and Microsoft Fabric.

Key Skills (Workday “What You Bring”)

Leadership Skills and Behaviors

• Creates a culture that relentlessly focuses on improving outcomes for customers, employees, and the communities we serve.
• Leads and influences technical teams across multiple squads, functions, geographies, and experience levels.
• Demonstrates commitment to Our Credo, Diversity, Equity & Inclusion by fostering an environment where diverse talent can thrive.
• Brings a strong customer-centric mindset and ensures the delivery of products that anticipate and address customer needs.
• Establishes trusted partnerships with architects, engineering leaders, product leaders, and business stakeholders.
• Coaches, develops, and mentors engineering talent while promoting accountability, ownership, and innovation.

Product / Digital Expertise

• Extensive experience leading Agile delivery organizations, including product development, governance, standards, and organizational change management.
• Deep technical expertise across Azure, Microsoft Fabric, Databricks, Power BI, Data Mesh, Data Federation, Data Modeling, Data Governance, Enterprise Data Management, AI Engineering, and Generative AI technologies.
• Strong understanding of cloud-native architectures, API-first design, distributed systems, and enterprise integration patterns.
• Expertise with modern SDLC practices, CI/CD pipelines, test automation, DevOps, containerization, Infrastructure as Code, and platform engineering.
• Proven ability to evaluate technical tradeoffs and guide teams toward scalable, maintainable solutions.

Domain Expertise

• Experience leading the selection, implementation, integration, and operation of enterprise data, analytics, AI, and digital platforms.
• Strong experience managing products and platforms throughout their lifecycle in complex, multi-team environments.
• Deep understanding of enterprise delivery practices including planning, dependency management, governance, compliance, quality management, and operational excellence.
• Ability to align technology investments with business strategy, value drivers, and industry trends.
• Demonstrated success driving measurable business outcomes through data, analytics, and AI solutions.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related field; Master’s degree preferred.
• 15+ years of experience in enterprise data engineering, technical architecture, analytics, AI platforms, and cloud engineering.
• Proven experience leading architecture decisions, technical strategy, and engineering standards across multiple teams and products.
• Hands-on expertise with Azure, Microsoft Fabric, Databricks, Power BI, and modern cloud-native technologies.
• Strong experience with Data Mesh, Data Federation, Data Products, Data Modeling, Data Governance, and Enterprise Data Management disciplines.
• Demonstrated expertise with Generative AI technologies including LLMs, RAG, vector databases, AI agents, prompt engineering, and enterprise AI architectures.
• Experience implementing MLOps, LLMOps, Responsible AI, model governance, and AI operationalization frameworks.
• Strong understanding of structured and unstructured data architectures supporting enterprise AI and intelligent automation.
• Exceptional communication, collaboration, and stakeholder management skills with the ability to influence both technical and non-technical audiences.
• Proven ability to lead through ambiguity and drive alignment across business and technology organizations.

Preferred Qualifications

• Experience operating in highly regulated industries with stringent security, privacy, compliance, and quality requirements.
• Experience partnering with ISRM, Quality & Compliance organizations, and audit functions to ensure operational readiness and control compliance.
• Experience with enterprise knowledge management platforms, document intelligence solutions, and semantic technologies.
• Familiarity with knowledge graphs, graph databases, vector platforms, enterprise search, and advanced AI retrieval strategies.
• Demonstrated experience establishing engineering observability, reliability engineering practices, Site Reliability Engineering (SRE), and operational excellence frameworks.
• Experience driving measurable business outcomes and value realization through enterprise data and AI initiatives.
• Experience leading enterprise AI transformation programs, AI platform strategy, and adoption of emerging AI technologies at scale.

Benefits

• Medical, dental, vision, life insurance, short- and long-term disability, business accident insurance, and group legal insurance.
• Consolidated retirement plan (pension) and savings plan (401(k)).
• Vacation – 120 hours per calendar year.
• Sick time - 40 hours per calendar year; for employees who reside in the State of Washington – 56 hours per calendar year.
• Holiday pay, including Floating Holidays – 13 days per calendar year.
• Work, Personal and Family Time - up to 40 hours per calendar year.
• Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child.
• Condolence Leave – 30 days for an immediate family member; 5 days for an extended family member.
• Caregiver Leave – 10 days.
• Volunteer Leave – 4 days.
• Military Spouse Time-Off – 80 hours.