Data Engineer II

About the job

The Data Engineering team within the SMART org supports development of large-scale data pipelines for machine learning and analytical solutions related to unstructured and structured data. You'll have the opportunity to gain hands-on experience on all kinds of systems in the data platform ecosystem. Your work will have a direct impact on all applications that our millions of customers interact with every day: search results, homepage content, emails, auto-complete searches, browse pages and product carousels and build and scale data platforms that enable to measure the effectiveness of wayfairs ad-costs , media attribution that helps to decide on day to day or major marketing spends.

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.