Principal Data Engineer

New Balance is hiring a Principal Data Engineer II to lead enterprise data infrastructure for the Global Data & Analytics team with deep Snowflake expertise and AI-assisted engineering workflows.

Responsibilities

• Lead architecture, design, and development of reliable data pipelines for acquiring, ingesting, transforming, and delivering data across on-premises, cloud, batch, streaming, and event-driven sources
• Define reusable architecture patterns and engineering standards for the platform
• Unify batch, streaming, and event-driven processing within a cohesive cloud data architecture with monitoring, alerting, recovery, and operational controls
• Partner with business and IT stakeholders and data consumers to define requirements, identify source systems and integration approaches, and model business and system processes using use case scenarios, workflow diagrams, and data models aligned to enterprise data architecture
• Design and deliver reusable, well-governed data products across business domains with data owners and consumers, covering requirements, quality standards, documentation, ownership, and operational expectations
• Lead technical design reviews and guide decisions across scalability, reliability, security, maintainability, performance, and cost optimization
• Apply practical AI capabilities to improve pipeline development, testing, and operations, including AI coding agents (e.g., Snowflake CoCo) and LLM-powered techniques (e.g., Snowflake Cortex AI Functions)
• Automate data-quality validation and source-to-target reconciliation using AI with appropriate security, governance, human review, and production controls
• Debug, profile, and optimize integrations and ETL/ELT processes to improve performance, reliability, and efficient resource consumption
• Drive process improvements by automating manual work, optimizing data delivery, and strengthening CI/CD and testing practices to improve scalability and supportability
• Document application and data architecture, engineering standards, operating procedures, technology decisions, and maintain operational runbooks; recommend practical improvements and alternatives
• Provide prompt production issue response and on-call support as needed, keep stakeholders informed, and surface delivery risks or obstacles with lead time
• Foster collaboration through open communication, technical mentorship, knowledge sharing, and succession planning; stay current with emerging data engineering and platform capabilities

Requirements

• Bachelor’s degree in Computer Science, Management Information Systems, or related field (or equivalent professional experience)
• 11-13 years of experience in data warehouse and data engineering development, including building, managing, and optimizing enterprise data pipelines in cloud computing environments
• Proven ability to lead architecture and development of complex data pipelines and integrations across multiple source systems, with strong knowledge of the software development life cycle
• Strong understanding of data architecture, data modeling, data quality, observability, and secure engineering practices
• Expert proficiency in SQL and Python, with strong analytical, troubleshooting, and problem-solving skills
• Deep experience with Snowflake data warehousing and data engineering capabilities, including performance optimization, cost-conscious design, and development using SQL, Python, and Snowpark
• Ability to translate business requirements into technical specifications, including data sources, integration methods, transformations, data models, validation controls, and operational requirements
• Experience designing and delivering reusable data products across multiple business domains, including modeling, pipeline development, quality controls, documentation, and operational support
• Experience with Azure data integration services, including Azure Data Factory and Azure Data Lake Storage or Azure Blob Storage
• Experience with data transformation and software delivery practices using tools such as dbt, GitHub, GitHub Actions, automated testing, and CI/CD
• Experience using AI coding agents to accelerate pipeline development and testing and applying LLM-powered techniques to automate data-quality validation or reconciliation in ELT pipelines
• Demonstrated technical ability, thoroughness, and accuracy; ability to analyze issues using technical databases and business application understanding to reach results-oriented conclusions
• Excellent written and verbal communication skills to explain technical concepts to technical and non-technical audiences, influence cross-functional decisions, and proactively raise risks and issues
• Demonstrated sense of urgency, initiative, and adaptability; sound judgment, attention to detail, required confidentiality, influencing and negotiation skills, and ability to mentor engineers

Technologies

• Snowflake
• SQL
• Python
• Snowpark
• Snowflake CoCo
• Snowflake Cortex AI Functions
• LLM
• ETL
• ELT
• Azure Data Factory
• Azure Data Lake Storage
• Azure Blob Storage
• dbt
• GitHub
• GitHub Actions
• CI/CD
• automated testing
• streaming
• event-driven

Benefits

• Comprehensive traditional benefits package including three options for medical insurance, plus dental, vision, life insurance, and 401K
• Online learning and development courses
• Tuition reimbursement
• $100 monthly student loan support
• Mentorship programs
• Yearly $1,000 lifestyle reimbursement
• 4 weeks of vacations
• 12 holidays
• Generous parental leave
• Flexible work schedule with North American hybrid model (in office three days per week: Tuesday, Wednesday, Thursday)
• Work from Anywhere (WFA) for four weeks per calendar year

Location and Pay Range

• Brighton, MA (hybrid)
• Annual base pay range: USD 138,500 - 207,500 (with intermediate range shown as $138,500.00 - $173,000.00 - $207,500.00)

Work Schedule Details

• In-office three days per week: Tuesday, Wednesday, and Thursday
• Work from Anywhere (WFA) for four weeks per calendar year