Data Analyst

Project Description

Client is seeking a technically strong Data Analyst to join our analytics team, reporting to our Senior Director of Data Analytics. This is a hands-on, full-stack role responsible for owning the complete data delivery chain from source data transformation and modeling through to business-facing reporting and dashboards in Sigma. Our team builds and owns the data layer and reporting tools that enable business stakeholders to perform their own analysis. You will own projects end to end, working closely with stakeholders to understand requirements and seeing them through to delivery independently.

Best described as an Analytics Engineer with some analytics responsibilities, focused on enabling the business to perform analysis rather than generating insights directly.

Duties/Day to Day Overview

• Own analytics and reporting projects end to end, from requirements gathering through source data transformation, modeling, and final delivery in Sigma.
• Write, optimize, and maintain complex SQL including stored procedures, views, and scheduled tasks in Snowflake to support robust, production-quality data pipelines.
• Design and implement data models and semantic layers that serve as the foundation for business reporting across merchandising, marketing, inventory, and operations.
• Build and maintain business-facing dashboards and reports in Sigma, designing for clarity, usability, and self-serve access by non-technical stakeholders.
• Validate and QA data at every stage of the pipeline, ensuring accuracy and reliability of outputs before delivery to stakeholders.
• Partner with business stakeholders to translate reporting requirements into technical specifications, managing expectations on scope, timelines, and tradeoffs throughout delivery.
• Document work clearly, follow established best practices for intake and delivery, and manage personal workload across multiple concurrent projects.
• Handle ad hoc and urgent data requests while maintaining quality and accuracy, flagging tradeoffs or risks proactively.
• Team is not primarily performing analysis. They are providing tools and data products that enable business users to analyze their own data.
• Team delivers artifacts to business units to support future projects.

Day to day

• 75% hands on keyboard / 25% meetings
• 8am PST standup - required to attend
• Can work local hours but must maintain a consistent schedule
• Meet with stakeholders to gather requirements along with Sean to hear from them directly and ask questions, summarize findings into actionable tasks, some UAT
• Jira and confluence, might give them a ticket and how to split it into lower level tickets and will be doing some of that and other development
• writing SQL, creating Sigma workbooks
• Writing queries to pull data from Snowflake - have a data eng team that writes pipelines to get data into Snowflake
• Most business logic in SQL queries and upstream in snowflake
  • Would get data from sourcetables and curated tables – not raw data – and would write their queries from those. Writing queries in snowflake (views/tables/tasks/store procedures).
• Sigma side (BI layer) – component of – need to learn the Sigma UI (should be easy enough).
  • doing their own QA - all peer reviewed

Top Requirements

• 2–4 years of experience in data analytics, business intelligence, or a related field; retail or e-commerce experience a plus.
• Advanced SQL skills including stored procedures, views, and query optimization; hands-on experience with Snowflake and a modern BI platform (Sigma preferred).
• Proven ability to design and implement data models and semantic layers that support reliable, scalable reporting.
• Comfortable owning projects end to end and working directly with business stakeholders to gather requirements and manage delivery.
• Experience building polished, user-facing dashboards and reports designed for self-serve use by non-technical business stakeholders.
• Able to manage personal priorities and delivery timelines in a fast-paced environment.
• Clear communication and documentation skills for both technical and non-technical audiences.
• Working knowledge of retail performance drivers across merchandising, marketing, inventory, and/or operations.
• Organized, proactive, and able to balance competing priorities while maintaining quality.
• End to end exposure to analytics workflow from post-ingestion data modeling through end-user consumption
• Analytics engineering background with experience around SQL, stored procedures, data modeling, and BI delivery (NOT A DATA ENGINEER)

SQL - must have

• Writing SQL queries to pull data from snowflake
• Familiarity with window functions, CTEs, joins, aggregators
• Familiarity with AI to help them, need foundational knowledge of SQL without it. More fluent in using AI to help their workflows, speed things up. Claude familiarity

Snowflake experience

• Build and maintain data assets within Snowflake after data ingestion is complete.

BI tools - Sigma, Tableau, or Power BI

• Writing store procedures and tasks. Using pipelines in their BI Layer
• Visualization is not required

QA experience

• Manual QA, ideally writing their own tests and have some documentation in place to support
• Retail experience
• Experience working with AI tools and incorporating them into daily workflow
• Good communication skills
• Ability to speak with stakeholders, gather requirements and turn into actionable tasks

Additional Qualifications

• Sigma - nice to have - A+
• Team provides self-serve analytics for teams who perform their own analysis