Software Engineer, Analytic Engineering

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over 2 years old

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Who We Are: 

The Fulfillment Platforms team is building the future platforms for intelligence and automation of the Wayfair supply chain.  The Analytic Engineering subgroup is focused on application development and delivery and works closely with the Model Execution Platform.

We innovate, productize, and scale sophisticated data and analytical systems to improve prediction and decision-making within supply chain operations.  Much of our work is first-of-a-kind due to the unique aspects of Wayfair’s e-commerce logistics network.  Team members generally multi-task across software engineering, algorithms, data engineering, and infrastructure.

Projects span each pillar of Wayfair’s logistics network:

  • Inventory management
  • Fulfillment center (warehouse) and home delivery operations
  • Transportation planning and routing (first / middle / last-mile)
  • International Supply Chain (including drayage)
  • Sales and Operations Planning (S&OP)

What You Will Do: 

  • Lead the building of cutting-edge data and analytical platforms that markedly increase automation and scalability in Wayfair’s logistics network
  • Partner closely with analytical teams in Operations Research, Data Science, Operations Analytics, Network Management, and Business Intelligence
  • Partner closely with functional engineering teams within Wayfair’s logistics network to design and integrate systems
  • Identify and implement innovative tools, technologies, and processes 
  • Promote a culture of engineering excellence and strengthen the technical expertise of  engineering and product teams across Wayfair
  • Drive improvements to the quality of your systems, both by improving them yourself and improving the technical ability of the team around you.

What You’ll Need:

  • Broad experience across technology and software engineering (guidance of 2-3 years related work experience)
  • Track-record of bringing new technical innovations to production environments
  • Current active hands-on development
  • Preferably, experience in a quantitative, algorithmic, or data-science related domain
  • Preferably, experience in big-data disciplines (data architecture, data engineering, databases), ideally with analytical workloads
  • Preferably, experience building or using distributed systems (i.e. Kubernetes, Spark, Hadoop, Airflow etc.)
  • Preferably, familiarity with operations research, machine-learning, optimization, or data-science techniques
  • Preferably, familiarity with Google Cloud Platform (GCP) and related GCP offerings
  • Nice to have, expertise in Python or Java
  • Nice to have, experience with various data serialization formats (i.e. Avro, Parquet, protobufs, etc.) and analytical databases (i.e. BigQuery, Presto, Hive, etc.)

About Wayfair Inc.

Wayfair is one of the world’s largest online destinations for the home. Whether you work in our global headquarters in Boston or Berlin, or in our warehouses or offices throughout the world, we’re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you’re looking for rapid growth, constant learning, and dynamic challenges, then you’ll find that amazing career opportunities are knocking.

No matter who you are, Wayfair is a place you can call home. We’re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair – and world – for all. Every voice, every perspective matters. That’s why we’re proud to be an equal opportunity employer. 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, or genetic information.