Zappos.com LLC

Business Intelligence, Business Intel Engineer, subsidiaries

Sr.BusinessIntelligenceEngineer,CustomerData&Analytics,CustomerStrategy

$143–194k New York, New York, United States FULL TIME
The Brief

“Sr. Business Intelligence Engineer, Customer Data & Analytics, Customer Strategy at Zappos.com LLC. Skills: Business Intelligence, Data Engineering, Customer Data, Analytics. Own the customer tables and customer attribute store. Define schema design”

Industry & Context.

Business Intelligence, Business Intel Engineer, subsidiaries
Problems you'll solve

Identify gaps in our data infrastructure; Identify gaps in the customer data

What They're Looking For.

Must Have

10+ years of professional or military experience, 5+ years of SQL experience, 1+ years of processing large, multi-dimensional datasets, Experience programming to extract, transform and clean large data sets, Experience with theory and practice of design of experiments and statistical analysis of results, Experience with AWS technologies, Experience in scripting for automation, Advanced SQL skills, 3+ years of developing automated reporting experience, Experience working directly with business stakeholders, Experience managing, analyzing and communicating results to senior leadership, Knowledge of data warehousing, Knowledge of data modeling

Nice to Have

Experience with Airflow, Experience with dbt, Experience with AWS Glue, Experience integrating third-party data sources with first-party customer data, Experience with customer segmentation frameworks, Experience with lifecycle analytics, Experience with Python for data analysis, Experience with R for data analysis, Experience with Python for automation, Experience with R for automation, Understanding of data governance, Understanding of data quality monitoring, Understanding of documentation best practices, Experience within e-commerce, Experience within retail, Experience with customer data platforms, Experience with customer attribute stores, Usage of generative AI tools, Willingness to learn effective prompting and evaluation practices, Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences

What You'll Do.

Own the customer tables and customer attribute store

Define data quality standards

Architect scalable data pipelines

Define SLAs for freshness and reliability

Drive the technical roadmap for the customer data

Build reporting tools

Maintain reporting tools

Lead deep dives with Customer Insights Managers

Measure lifecycle and acquisition impact

Surface actionable trends

Own third-party data sources and tooling

Own integrations connecting external data into our customer

Define and execute the strategy for integrating third-party

Operationalize models

Design feature tables

Design pipeline architecture

Design reporting layers

Bring predictive work into production

Drive measurement infrastructure

Build foundations for holdout analysis

Build foundations for test/control reporting

Build foundations for performance tracking

Develop reusable frameworks

Develop self-service tools

Scale the team's analytical capacity

Identify gaps in the customer data

Influence priorities across teams to improve analytical infrastructure

How You'll Work.

Team & Collaboration

Connective tissue between teams; Partner with Data Engineering; Work closely with Customer Insights Managers; Work closely with Data Scientists; Work with Customer Insights; Work with Data Science; Work with Lifecycle Marketing; Work with Finance; Work with Engineering

Communication Scope

Communicating results to senior leadership

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