Data Engineer - L2

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 runs the largest custom e-commerce large parcel network in the United States, approximately 1.6 million square meters of logistics space. The nature of the network is inherently a highly variable ecosystem that requires flexible, reliable, and resilient systems to operate efficiently. 

We are looking for a passionate Backend Software Engineer to join the Fulfillment Optimization team. This team builds the platforms that determine how customer orders are fulfilled, optimizing for Wayfair profitability and customer delight. A big part of our work revolves around enhancing and scaling customer-facing platforms that provide fulfillment information on our websites, starting at the top of the customer funnel on the search pages all the way through orders being delivered. Throughout this customer journey, we are responsible for maintaining an accurate representation of our dynamic supply chain, determining how different products will fit into boxes, predicting how these boxes will flow through warehouses and trucks, and ultimately surfacing the information our customers need to inform their decision and the details our suppliers and carriers require to successfully execute on the promises made to our customers. We do all of this in milliseconds, thousands of times per second.

About the Role: 

As a Data Engineer, you will be part of the Data Engineering team with this role being inherently multi-functional, and the ideal candidate will work with Data Scientist, Analysts, Application teams across the company, as well as all other Data Engineering squads at Wayfair. We are looking for someone with a love for data, understanding requirements clearly and the ability to iterate quickly. Successful candidates will have strong engineering skills and communication and a belief that data-driven processes lead to phenomenal products. 

What you'll do: 

• Build and launch data pipelines, and data products focussed on SMART Org. 
• Helping teams push the boundaries of insights, creating new product features using data, and powering machine learning models.
• Build cross-functional relationships to understand data needs, build key metrics and standardize their usage across the organization. 
• Utilize current and leading edge technologies in software engineering, big data, streaming, and cloud infrastructure 

What You'll Need: 

• Bachelor/Master degree in Computer Science or related technical subject area or equivalent combination of education and experience 3+ years relevant work experience in the Data Engineering field with web scale data sets. 
• Demonstrated strength in data modeling, ETL development and data lake architecture.
• Data Warehousing Experience with Big Data Technologies (Hadoop, Spark, Hive, Presto, Airflow etc.).
• Coding proficiency in at least one modern programming language (Python, Scala, etc)
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing and query performance tuning skills of large data sets.
• Industry experience as a Big Data Engineer and working along cross functional teams such as Software Engineering, Analytics, Data Science with a track record of manipulating, processing, and extracting value from large datasets.
• Strong business acumen. Experience leading large-scale data warehousing and analytics projects, including using GCP technologies – Big Query, Dataproc, GCS, Cloud Composer, Dataflow or related big data technologies in other cloud platforms like AWS, Azure etc. 
• Be a team player and introduce/follow the best practices on the data engineering space.
• Ability to effectively communicate (both written and verbally) technical information and the results of engineering design at all levels of the organization.

Good to have : 

• Understanding of NoSQL Database exposure and Pub-Sub architecture setup.
• Familiarity with Bl tools like Looker, Tableau, AtScale, PowerBI, or any similar tools.