We are hiring a Lead Business Intelligence Engineer for our Personalization team in Seattle, WA. In this position, you will help us build scalable, robust analytics solutions for Personalization at Chewy. You will demonstrate a passion for delivering outstanding customer experience, experience of building scalable solutions and will bring communication skills that allow you to instill trust in the team that you are working with.
Millions of pet parents with unique needs visit Chewy.com looking for products for their beloved pets. We have the task to decide what products would be most useful to them and help them discover those products. How do we do this?
Meet Personalization team @ Chewy. We use best of machine learning techniques and continuously test the outcomes to simplify product discovery for pet parents looking for their pet needs on Chewy.com. Our exceptional multi-disciplinary team of data scientists, data engineers, software engineers and product managers work together to power personalized recommendations and product discovery for pet parents. Our team has single threaded ownership of the space allowing us to decide impactful products that we can experiment, measure with metrics and deliver at a fast pace.
We are seeking:
We are seeking an individual with excellent statistical and analytical abilities, data engineering skills and importantly an uncanny knack and passion for turning qualitative analysis and observations into diagnostics and metrics. The successful candidate will be a self-starter and someone who thrives in a fast-paced and ever-changing environment, driven by a desire to innovate and move fast. You know and love working with business intelligence tools, can model multidimensional datasets, and can partner with customers to answer key business questions. You are analytical and creative, and you don't quit.
You will also have the opportunity to display your skills in the following areas:
1. Be a thought leader: Interface with business partners, architect, design, implement, and support BI projects & tools that derive customer shopping insights and shape business decisions.
2. Operate at Depth , Raise the bar and insist on highest quality : Recognize and adopt best practices in analysis and reporting, data integrity, test design, analysis, validation, and documentation.
3. Deliver Results: Be inspired by the motto of Customer First, use outstanding business acumen, technical and analytical skills to drive real, actionable results.
What You’ll Do:
- Design, develop, implement, test, document, and operate large-scale, high-volume, high-performance data models, reports/dashboards/BI solutions for analytics and deep learning
- Implement data ingestion routines both real time and batch using best practices in data modeling, ETL/ELT processes
- Provide on-line reporting and analysis using business intelligence tools and a logical abstraction layer against large, multi-dimensional datasets and multiple sources
- Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions that work well within the overall data architecture
- Produce comprehensive, usable data set documentation, metadata, BI reports, Dashboards and insights
What You’ll Need:
- Candidate must possess a Bachelor’s degree in Computer Science, or related field, or equivalent experience
- 6+ years of experience with detailed knowledge of BI data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools
- 4+ years of experience with BI/visualization tools like Tableau/BO/OBIEE etc.
- 3+ years of work experience in building self-serve BI solutions, canned reports and enterprise level BI solutions
- 3+ years of experience with data modeling in large Data warehousing, data lake environment
- 2+ years of data science experience with building regression, classification models
- Exposure to Big Data stack environments (EMR, Hadoop, MapReduce, Hive)
- Good analytical skills with excellent knowledge of SQL and advance SQL
- Excellent communication skills, both written and verbal
- Experience with A/B Testing & Optimization techniques
- Experience in gathering requirements and formulating business metrics for reporting
- Experience building on AWS QuickSight, ElasticCache etc
- Experience with statistical models and building predictive models from scratch
- Experience with building NLP and sentiment analysis