Data Engineer II, Global Supply Technology @ Wayfair
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About Data Engineer II - Global Supply Technology
Wayfair is the largest custom e-commerce large parcel network in the United States with 1.6 million square meters of logistics space. Based in Bangalore, India, this role is part of the Data Engineering team within Global Supply Technology (GST), fulfilling large-scale data needs for data scientists, machine learning, and analytics across batch and real-time use-cases.
What You’ll Do
You will design, build, and launch new data models, pipelines, and products focused on Search and Recommendations. You will work cross-functionally with data scientists, analysts, application teams and other Data Engineering squads to push analytical insights and power machine learning models.
- Drive new data model and pipeline development.
- Collaborate across teams to standardize key metrics.
- Utilize leading technologies in big data and cloud infrastructures.
- Create and maintain a curated data lake.
- Apply strong engineering and communication skills.
Who We Are
Wayfair is one of the world’s largest online destinations for the home. With a commitment to innovative technology and creative problem-solving, it offers an environment of rapid growth, constant learning, and dynamic challenges.
Qualifications
- Bachelor/Master degree in Computer Science or related field.
- 3+ years of web scale data experience as a Data Engineer.
- Proficiency in an object-oriented or scripting language (Java, Scala, Python) and SQL.
- Experience with Big Data tools such as Hadoop, Spark, Hive, Presto, and Airflow.
- Familiarity with cloud platforms (GCP, AWS, or Azure) and BI tools like Looker or Tableau (preferred).
- Strong understanding of data structures, algorithms, and data architectures.
- Excellent communication and presentation skills.
Key skills/competency
Data Engineering, Big Data, Cloud, SQL, Python, Hadoop, Spark, Data Pipelines, Machine Learning, Analytics
How to Get Hired at Wayfair
🎯 Tips for Getting Hired
- Research Wayfair's culture: Explore their mission and innovation on career pages.
- Customize your resume: Highlight data engineering projects and skills.
- Emphasize technical expertise: Detail your experience with big data tools.
- Prepare for behavioral interviews: Reflect on cross-team collaboration scenarios.