Director, Data Engineering (AI)

TL;DR

Director, Data Engineering (AI): Building and leading enterprise cloud data platforms that power analytics, AI/ML, operational reporting, and digital products with an accent on scalable architecture, governance, reliability, and DataOps. Focus on modernizing legacy environments, enabling real-time data capabilities, and developing high-performing engineering teams that deliver secure and measurable business value.

Location: Needham, Massachusetts, United States

Salary: $175,500–$235,000 USD annually

Company

Global product design and technology company developing consumer lifestyle products across multiple categories and selling through retailers, online channels, and distributors worldwide.

What you will do

• Define and execute the enterprise data engineering strategy in alignment with the digital transformation roadmap.
• Build, lead, coach, and develop a high-performing organization of data engineers and technical leaders.
• Architect and evolve cloud-based data platforms supporting analytics, AI/ML, reporting, and digital products.
• Establish standards for data architecture, ingestion, transformation, orchestration, observability, governance, lineage, and quality.
• Lead legacy modernization, DataOps adoption, platform reliability initiatives, and complex architecture reviews.
• Manage technology investments, vendors, budgets, roadmaps, and executive communication.

Requirements

• Bachelor’s degree in computer science, information systems, data engineering, software engineering, or a related technical discipline.
• 10+ years of progressive experience in data engineering, data platform engineering, software engineering, or related fields.
• Significant experience leading and developing high-performing engineering teams.
• Proven success delivering enterprise-scale cloud data platforms and modern data architectures in complex organizations.
• Expertise with Azure, AWS, or Google Cloud, plus SQL, Python, Spark, distributed data processing, and ELT/ETL architectures.
• Experience with DataOps, CI/CD, infrastructure as code, automated testing, data governance, metadata, lineage, data quality, streaming, APIs, and AI/ML pipelines.

Nice to have

• Master’s degree in computer science, engineering, information systems, or a related discipline.
• Experience in consumer products, retail, manufacturing, or digital commerce.
• Experience leading enterprise digital transformation initiatives.
• Experience supporting AI and machine learning platforms at scale.

Culture & Benefits

• AI-native culture focused on experimentation, continuous improvement, and measurable impact.
• Medical, dental, and vision insurance, flexible spending accounts, and HSA contributions.
• 401(k) plan with matching, employee stock purchase program, life and disability insurance.
• Paid time off, company holidays, parental leave, and backup childcare and eldercare days.
• Learning programs, wellness initiatives, product discounts, and additional employee support benefits.