Wayfair believes that everyone should live in a home they love. Utilizing technology and innovation, Wayfair enables shoppers to find what they want from millions of items in home furnishings, décor, home improvement, housewares, and beyond, quickly and easily. Wayfair is dedicated to delivering delight to its customers at every stage, reinventing the way people shop for their homes - from product exploration to final delivery.
Analytics Engineers at Wayfair are not only skilled in quantitative analysis and programming, but they also construct fast and scalable solutions for the organization. They tackle complex challenges using critical thinking, thrive in a fast-paced environment, and are looking for a high-growth opportunity where they will make an immediate impact. For motivated individuals just entering the workforce or with prior professional experience, there are ample opportunities.
You'll join the Global Analytics Tech team, which concentrates on propelling the design, creation, and handling of the corporate infrastructure and key performance indicators that bolster our operations teams and our business strategy, primarily influenced by the convergence of technology and business.
Whether you are building data warehouses, scalable data structures, analyzing process performance, troubleshooting issues, or building proactive monitoring systems, you'll utilize leading-edge technology and multi-terabyte datasets.
This position is a hybrid role, with a requirement to be in the office from Monday to Thursday.
What You'll Do:
- Contribute to the design, development, and maintenance of data warehouses, pipelines, and ETL (Extract, Transform, Load) processes.
- Collaborate with data engineers and analysts to comprehend data needs, and ensure data availability for examination.
- Work with a variety of data storage and processing technologies, including Google SQL.
- Help clean, preprocess, and modify data from a multitude of sources to make it suitable for analysis.
- Assist in the creation and optimization of databases and data warehouses.
- Help diagnose and solve data-related complications and bottlenecks.
- Learn and apply best practices in data engineering, data modeling, and data governance.
- Document data engineering processes and workflows for future reference.
- Collaborate with cross-functional teams to support data-driven campaigns and projects.
What You’ll Need:
- A Bachelor's or Master's degree in Computer Science, Computer Engineering, Mathematics, Statistics, Information Systems or other quantitative STEM field with a strong academic history.
- Experience in engineering roles focusing on backend data warehousing. Added value if quantitative analysis experience.
- A strong interest in data engineering, big data technologies, and data processing.
- Knowledge of DBT/Dataforms, BigQuery, Airflow, GCP, and BI tools.
- Proficiency in Python programming.
- A basic understanding of data management concepts and databases.
- Hands-on experience in conducting quantitative analyses on large datasets, and experience with data modeling and visualization tools.
- Proficient knowledge of SQL, Python, and Bash programming languages, including understanding of Git for version control.
- A solution-oriented and intellectually curious mindset - We value fast results, project scoping, and continuous learning.
- Excellent written and verbal communication skills and a team player, with a highly collaborative attitude. We communicate effectively without sugarcoating and focus on helping the team on the most valuable projects.
- Previous experience or coursework related to data engineering is desirable.
Assistance for Individuals with Disabilities:
Wayfair is fully committed to providing equal opportunities for all individuals, including those with disabilities. In line with this commitment, Wayfair makes reasonable accommodations for known physical or mental limitations of qualified individuals with disabilities unless doing so would impose undue hardship on business operations. If you require reasonable accommodation to participate in the job application or interview process, please inform us by completing our Accommodations for Applicants form.
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