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Applications open Full-Time Job

Software Engineer II - Java Backend

Wayfair

  • Bengaluru, India
  • Competitive Package
  • 3–5 Years
  • Posted Yesterday
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About the role

Candidates for this position are preferred to be based in Bangalore, India and will be expected to comply with their team's hybrid work schedule requirements.

Who We Are

Wayfair helps customers find the right products for their homes. Our engineering teams build the systems and experiences that make each customer's shopping journey personal across Wayfair's digital storefronts.

The Customer Data Platform team builds and runs the systems behind Wayfair's single view of the customer. We resolve customer identity across devices and channels, combine first-party and third-party data into rich customer profiles, and deliver those profiles and insights at scale. They power personalisation, recommendations, marketing and analytics across the company.

We work with software engineering, product, data science and analytics teams to build reliable, privacy-conscious data products.

What You'll Do

  • Build and maintain backend services and high-throughput, low-latency APIs that serve customer profiles, attributes and insights to personalisation, recommendation and marketing systems.
  • Design and build well-tested batch and real-time data pipelines that collect, enrich and maintain customer data profiles from many sources.
  • Develop and improve identity resolution systems that link customer interactions across devices, sessions and channels into a unified customer view.
  • Partner with data scientists to put ML-driven customer features into production, such as embeddings, affinity and propensity scores, and segments, and make them available to downstream systems.
  • Own scoped technical problems from design through implementation, testing, deployment and ongoing maintenance.
  • Make data more reliable, fresh, high-quality and observable. Investigate production and data issues and follow through on fixes.
  • Help build privacy, consent and data-governance practices into how customer data is collected, stored and used.
  • Contribute to technical designs, code reviews, documentation and operational practices.
  • Use metrics, experiments and feedback from partner teams to find ways to improve the platform's quality and impact.

What You'll Need

  • A bachelor's degree in Computer Science, Computer Engineering, or a related field, or an equivalent combination of education and experience.
  • 3–5 years of professional software development experience.
  • Strong proficiency in at least one backend programming language, such as Java or Python.
  • Experience building or maintaining APIs, services or distributed applications that handle large volumes of data.
  • A solid foundation in data structures, algorithms, software design and automated testing.
  • Experience with relational and non-relational databases, data modelling and writing maintainable data-access code.
  • Familiarity with production software practices, including version control, CI/CD, monitoring and debugging.
  • Clear communication skills and the ability to work well with both technical and non-technical teams.

Preferred Qualifications

  • Experience with customer data platforms, identity resolution, entity matching or customer 360 / master data systems.
  • Experience building large-scale data pipelines with tools such as Kafka, Spark, Dataflow, Airflow or BigQuery.
  • Familiarity with ML-powered personalisation, such as feature stores, customer embeddings, segmentation or recommendation systems.
  • Understanding of data privacy and consent requirements (for example GDPR or CCPA) and of how to handle PII responsibly.
  • Experience with cloud platforms, containers and orchestration technologies such as GCP, Docker or Kubernetes.
  • Experience supporting production services, including taking part in an on-call rotation.

Assistance For Individuals With Disabilities

Wayfair is fully committed to providing equal opportunities for all individuals, including individuals with disabilities. As part of this commitment, Wayfair will make reasonable accommodations to the known physical or mental limitations of qualified individuals with disabilities, unless doing so would impose an undue hardship on business operations. If you require a reasonable accommodation to participate in the job application or interview process, please let us know by completing our Accomodations for Applicants form.

Need Technical Assistance?

For more information about applying for a career at wayfair, visit our FAQ page here.

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 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, genetic information, or any other legally protected characteristic.

Your personal data is processed in accordance with our Candidate Privacy Notice (https://www.wayfair.com/careers/privacy). If you have any questions or wish to exercise your rights under applicable privacy and data protection laws, please contact us at dataprotectionofficer@wayfair.com.

The above base pay range may vary depending on location, job-related knowledge, skills and experience. For internal candidates, compensation determinations will be made based on your current position / level, your location, and the new position according to Wayfair's internal mobility policy. As you move through the internal interview process, your recruiter will be able to provide additional details regarding your specific compensation.

Please note, the terms of internal offers, including the salary offered, are not negotiable.

Eligibility & process

Who can apply

Seniority: Associate. Employment type: Full-time

Skills & stack

Python Java GCP Docker Kubernetes CI/CD Apache Kafka Machine Learning

Selection process

Details are shared by the recruiter after shortlisting.

Prep kit

19 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Python, Java, GCP, Docker, Kubernetes, CI/CD, Apache Kafka, Machine Learning) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion Wayfair Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 4
What is the bias-variance tradeoff and how do you prevent overfitting? Answer
Model answer: High bias leads to underfitting (oversimplified model), high variance leads to overfitting (captures noise). Mitigate using L1/L2 Regularization, Dropout, Cross-Validation, and data augmentation.
Explain the difference between Precision, Recall, and F1-Score. Answer
Model answer: Precision = TP / (TP + FP) (correctness of positive predictions). Recall = TP / (TP + FN) (coverage of actual positives). F1-Score is the harmonic mean of Precision and Recall.
How does Gradient Descent work and what is the role of Learning Rate? Answer
Model answer: It optimizes loss functions by iteratively moving weights in the direction of negative gradient. A large learning rate may overshoot the minimum; a small rate causes slow convergence.
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer
Model answer: Supervised uses labeled data (X -> y). Unsupervised finds hidden patterns in unlabeled data (clustering/PCA). Self-supervised generates labels from input data (e.g. masked language modeling in BERT/Transformers).
Behavioural & HR questions 3
Why do you want to join Wayfair as a Software Engineer II - Java Backend?
Highlight Wayfair's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Wayfair Competitive Package
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