Associate Director Software Engineering - Data Platform

Wayfair is looking for an experienced Technology Leader to own the vision, strategy and execution of Wayfair’s Data Platform technology that power experiences across all of our retail brands (Wayfair, Perigold, All Modern, Joss & Main, Birch Lane) and geographies (currently 4 countries - US, CAN, UK, IE). In 2024, Wayfair generated ~$12 billion in net revenue which at our $500+ billion (and growing) total addressable market means we are just getting started.

This team’s mission is to build a data landscape and culture that maximizes the ease of deriving actionable insights by creating platforms that provide easy access to usable and trustworthy data. This role empowers a cross-functional team of engineers, product managers, and technical program managers to build and transform our data ecosystem, enabling them to leverage it in a scalable, observable manner with clear ownership and quality controls.

You will lead the shift from a centrally managed data platform to an integrated, decentralized ownership ecosystem. You will drive the modernization of our core infrastructure while ensuring our data foundations are ready for the next generation of uses.

• Drive a world-class Data Platforms, setting its strategy that shifts the organization from a centralized model to a producer-owned, self-serve ecosystem that improves trust, operability, and cost efficiency.
• Own the implementation, and manage real-time messaging, orchestration and analytics layers with cloud-native solutions, ensuring a fault-tolerant, highly observable, and auditable platform for event processing.
• Lead the modernization of legacy data tooling by standing up cloud-native solutions for orchestration, ingestion, complete, migrating from legacy systems when necessary
• Champion decentralized but empowered ownership of data by building the underlying capabilities (controls mechanisms, lineage, observability) and cultural frameworks that empower data producers to own and operate their assets with accountability.
• Enable AI and Agentic readiness by establishing patterns and tools, making it easy to stand up AI use cases
• Drive systemic cost management and efficiency across storage and compute landscapes, partnering with cross-functional teams for optimized solutions
• Collaborate effectively with senior partners across Product, Engineering, Science, and Finance to translate complex data ecosystem needs into high-value platform investments.
• Foster a team culture of high accountability, trust, and empowerment, specifically bridging the gap between deep data expertise and producer user experience.
• Lead multiple teams of engineers working on different facets of this platform

• 16+ years of global data platforms engineering leadership experience.
• Deep understanding and experience working with different data landscape/architectures, specifically with shifting from monolithic or centralized data models to decentralized (Data Mesh/Data Fabric) architectures.
• Expertise in one or more public clouds (Google, Azure, etc) with deep understanding about their data technologies and how to solve problems for a diverse set of consumers with such solutions
• Hands on experience working with one or more of the following, Python, Java, orchestration patterns & tools, Data warehouse/lakehouse architecture, OLAP, dimensional modeling, managing and scaling real-time systems (e.g., Kafka, Kinesis, Beam, Storm or similar), and other systems such as Postgres, SQL Server or similar, Spark/Dataproc, Big Query, Aerospike, Big Table, Redis, etc.
• Demonstrated understanding of managing costs and optimization strategies with large-scale data systems, balancing performance with storage/compute efficiency.
• Track record of navigating complex organizational change, driving the cultural shifts necessary to make technology investments deliver value for the business
• Communication skills with the ability to rally cross-functional teams on the strategy, implementation, and a joint approach with clear ownership and accountability.
• Proven experience scaling developer-facing data platforms, treating the platform as a product with a focus on developer velocity and self-service.

We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, genetic information, or any other legally protected characteristic.