Cloud Data Engineer II, Supplier Advertising

At Wayfair, our Data Engineering team is the driving force behind our data-driven eCommerce enterprise. We thrive in a fast-paced environment, constantly iterating on complex business problems. Our efforts in data Engineering play a pivotal role in expanding our market share in the $800 billion home goods market. Each day, we process billions of data points on how people select items for their homes, shaping our business strategies and decisions. We're at the forefront of building state-of-the-art data platforms that empower advanced analytics and insights across our business and analytics teams. 

As a cloud data engineer II, you will be a hands-on developer who designs and delivers Data Warehouses, Data Lakes, Self-service tooling, Real-time streaming, and Big Data Solutions for our rapidly growing Supplier Advertising. Working within the supplier advertising organization, this individual will closely partner with business, product managers, and engineering leaders to build data platforms that enable these goals. You will be instrumental in building out the data pipelines to ensure our data is generated, transformed, and mutated over time, working to build a cohesive, scalable, accurate, and performant foundational source of truth upon which all data scientists, machine learning and analytics across the company will be built. 

What You'll Do

• Build data pipelines to assemble large, complex sets of data that meet non-functional and functional business requirements
• Deliver Data Engineering capabilities for streaming and batch-based data ingestion, enrichment, and aggregation. 
• Design and develop sophisticated data models and visualizations that support multiple use cases across different products or domains.
• Helping teams push the boundaries of analytical insights, creating new product features using data, and powering machine learning models
• Define and manage SLA for all data sets in allocated areas of ownership.
• Work closely with the GST data engineering group, SMEs within Supplier Advertising, and other technology partners to develop & execute the data architecture roadmap for different functional areas
• Mentor and grow the technical skills of engineers across multiple sprint teams by giving high-quality feedback in design and code reviews and providing training for new methods, tools, and patterns
• Collaborate with your stakeholders and other business analytics team leaders 

What You Have [ Note - Overall experience level varies based on role requirement specified in Surge Contractor Request ]

• Bachelor's or Masters in Computer Science, Computer Engineering, Statistics, or another quantitative discipline
• 3+ years of experience in Data Engineering roles (including internships)
• Expertise in at least one object-oriented or scripting language (Java, Scala, Python, etc.) and comfortable working with SQL
• 1+ years' experience with schema design and dimensional data modeling
• Experience building and optimizing 'big data' data pipelines, architectures, and data sets 
• Experienced developing in cloud platforms such as Google Cloud Platform (preferred), AWS, Azure, or Snowflake at scale. ( GCP is preferred; GCP certification is even better) 
• Experience with real-time data streaming tools like Kafka, Kinesis, Apache Storm, or any similar tools
• Experience in designing data engineering solutions using open source and proprietary cloud data pipeline tools such as Airflow, dbt, Glue, and Beam
• Experience in the development of custom-built BI and big data reporting solutions using tools like Looker, DataStudio, or any similar tools
• Experience with code management tools (e.g., Git, SVN) and DevOps tools (e.g., Docker, Jenkins)
• Excellent communication and presentation skills, strong business acumen, critical thinking, and ability to work cross-functionally through collaboration with engineering and business partners
• Ability to learn quickly and drive deliverables while maintaining ownership/bias.
• A team player who is at ease delivering in a group setting.

What we'd love to see (but isn't required)

• Advertising or E-commerce analytics experience is a strong plus
• Prior experience in data science or closely related quantitative field