Software Engineer III - Data Engineering

As a Data Engineer, you will be part of the data engineering team. This role is inherently multi-functional, and the ideal candidate will work with client experience, data scientists, analysts, and 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, the ability to handle ambiguous requirements, and the ability to iterate quickly. Successful candidates will have strong engineering and communication skills and a belief that data-driven processes lead to phenomenal products.

Responsibilities:

Build and launch data pipelines and data products focused on SMART Org.

Help 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.

Requirements:

Bachelor's/Master's degree in computer science or a related technical subject area or an equivalent combination of education and experience.

6+ years of 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 for large data sets.

Industry experience as a Big Data Engineer and working with cross-functional teams such as Software Engineering, Analytics, and 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 BigQuery, 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 in 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 BI tools like Looker, Tableau, AtScale, Power BI, or any similar tools.