Associate Director, Engineering – Data Platforms

Associate Director, Engineering – Data Platforms (L5)

Who We Are

Wayfair operates at a massive scale across e-commerce, logistics, and customer experiences—powered by data. Our Data Platforms organization builds the foundational capabilities that make data trusted, discoverable, secure, and easy to use across the company.

We design and deliver core platform products including Data Lake & Warehouse foundations, batch and real-time data processing, self-service tooling, governance and lineage, data quality/observability, and scalable compute for analytics and ML —using modern cloud and open-source technologies.

We’re looking for a senior engineering leader to set direction, grow talent, and scale adoption of Wayfair’s data platform capabilities across our engineering and business ecosystem.

What You’ll Do

Pod Leadership & Strategic Direction

• Define and execute the charter for a Data Platforms Pod consisting of 2–4 atomic teams , aligned with broader org strategy and Wayfair Strategic Technology Objectives (STOs).
• Own measurable outcomes for the data platform across pipeline success rates, freshness/latency SLAs, data quality, cost-to-serve, and self-service adoption , driving improvements through platform standards and automation.
• Identify and manage cross-pod and cross-functional dependencies (Analytics, Product, ML, Security, Infra, Platforms), driving cohesive delivery and reducing fragmentation.
• Create clarity in ambiguous spaces: shape roadmap, align stakeholders, and drive execution across multiple teams.

Platform-as-a-Product Leadership

• Build and scale Platform-as-a-Product offerings that enable self-service data development: standard patterns, templates, APIs/SDKs, and paved-road workflows.
• Drive a strong platform product discipline: customer empathy (internal users), adoption strategy, documentation, enablement, and feedback loops .
• Establish and evolve platform metrics such as data freshness/latency SLAs, pipeline success rates, cost-to-serve, time-to-onboard, and self-service adoption .
• Partner with Product and stakeholders to translate business needs into platform capabilities that unlock faster decisioning and better customer outcomes.

Technical Strategy & Architecture

• Provide technical leadership across:
• Batch ETL/ELT and orchestration patterns
• Streaming and real-time processing foundations
• Warehouse and lakehouse architecture and modeling (e.g., star/snowflake, OLAP)
• Metadata, catalog, lineage, and governance capabilities
• Data quality and platform observability (pipeline reliability, schema drift, SLA monitoring)
• Security and privacy-by-design (access controls, auditing, data protections)
• Co-create and review technical artifacts: design docs, architecture reviews, technical RFCs, and post-incident learnings.

Operational Excellence & Cost Stewardship

• Champion engineering best practices for platform resilience: automation, standardized runbooks, incident response, and continuous improvement.
• Drive proactive operational health: reliability targets, on-call readiness, and reductions in repeated toil.
• Influence FinOps for data : capacity planning, cost controls, chargeback/showback approaches, and optimization initiatives.

People Development & Team Building

• Lead and develop engineering managers and senior ICs; create growth paths and raise the bar on technical and leadership excellence.
• Foster a high-trust, inclusive culture focused on outcomes, continuous learning, and pragmatic decision-making.
• Coach teams through tradeoffs, prioritization under ambiguity, and delivery of capabilities with broad organizational impact.

Stakeholder Engagement & Influence

• Represent Data Platforms in cross-functional and leadership forums—communicating strategy, progress, risks, and tradeoffs clearly.
• Build strong partnerships across Engineering, Analytics, ML, Security, and Business to drive adoption and align priorities.
• Influence with and without authority—aligning diverse stakeholders around platform standards and shared goals.

What You’ll Need

• 16+ years of software/data engineering experience, including 10+ years in technical leadership roles and 5+ years leading managers (or equivalent scope).
• Proven experience leading multi-team initiatives and owning outcomes for foundational platforms used by many teams.
• Strong expertise in modern data platform domains, including:
• ETL/ELT development (Python, Java, or similar) and orchestration patterns
• Cloud-based data platforms at scale ( GCP preferred , also AWS/Azure; Snowflake experience a plus)
• Data warehouse/lakehouse architecture , OLAP, dimensional modeling (star/snowflake)
• Streaming / real-time systems (e.g., Kafka, Kinesis, Beam, Storm or similar)
• Big data processing (e.g., Spark, Hadoop ecosystem; NoSQL like Cassandra/MongoDB as relevant)
• A strong track record of building self-service developer platforms (tooling, APIs, templates, paved roads) and driving adoption.
• Experience establishing operational rigor: platform SLOs/SLAs, monitoring, incident response, automation, and post-incident improvements.
• Excellent communication and stakeholder management skills, including translating between business needs and technical strategy.
• Bachelor’s or Master’s in Computer Science, Engineering, Statistics, or another quantitative discipline (or equivalent experience).

Nice to Have

• Experience enabling BI and analytics tools (e.g., Looker, Power BI, or similar) through well-architected semantic layers and governed datasets.
• Experience with data governance and privacy programs (catalog, lineage, access models, auditing).
• Prior e-commerce or high-scale logistics domain experience.
• Hands-on familiarity with ML/feature platforms and analytic engineering practices.

Why You’ll Love This Role

• You’ll shape the core data foundation that powers decision-making, analytics, and machine learning at Wayfair.
• You’ll lead a high-impact pod building platform products used across the company.
• You’ll operate at the intersection of technical strategy, org leadership, and business outcomes —with the mandate to simplify, standardize, and accelerate how Wayfair uses data.