Senior Analytics Engineer

Overview

We’re seeking a hands-on Senior Analytics Engineer to own and strengthen our commercial data environment. This role will build reliable data pipelines, develop scalable data models, improve data quality, and make business-critical information more accessible across the organization.

Working with data from e-commerce platforms, retail partners, marketing channels, and financial systems, you’ll transform complex, multi-source data into trusted datasets, reporting tools, and actionable insights. You’ll work extensively with SQL, dbt, and Python to create reliable data workflows that support commercial reporting, forecasting, and performance analysis.

A key focus of this role is enabling self-service analytics and AI-ready data infrastructure through well-defined metrics, documented business logic, and governed data models. The ideal candidate combines strong technical expertise with commercial judgment, excellent communication skills, and the ability to independently turn business needs into scalable technical solutions.

Key Responsibilities

Data Engineering & Modeling

Own and continuously improve the commercial data environment, including data pipelines, transformations, analytical models, and data marts.

Build and maintain scalable, production-ready data models using SQL and dbt or comparable transformation frameworks.

Develop reliable data workflows that support reporting, forecasting, and business decision-making.

Data Integration & Management

Integrate, standardize, and reconcile data from e-commerce platforms, retail partners, marketing channels, financial systems, APIs, third-party connectors, and structured files.

Ensure data from multiple sources is consistent, accessible, and aligned with business requirements.

Develop automated solutions to reduce manual reporting and improve operational efficiency.

Data Quality & Reliability

Establish and maintain data tests, monitoring processes, and reconciliation procedures.

Investigate and resolve data discrepancies across source systems, pipelines, transformation logic, and downstream reports.

Maintain high standards for data accuracy, consistency, reliability, and usability.

Analytics & Reporting

Develop trusted datasets, dashboards, and analytical tools that enable teams to answer recurring business questions independently.

Build reporting solutions across products, retailers, countries, sales channels, and stores to support omnichannel performance analysis.

Support commercial forecasting, sales performance monitoring, customer analytics, and profitability reporting.

AI Readiness & Analytics Enablement

Establish clear metric definitions, business logic, documentation, and semantic models.

Develop governed, well-structured datasets that support self-service analytics and AI-enabled reporting.

Improve data accessibility and help teams use reliable information to make informed decisions.

Cross-Functional Collaboration

Partner with Digital, Direct-to-Consumer (DTC), Retail, Marketing, Finance, and Leadership teams to understand business needs and translate them into technical solutions.

Communicate data definitions, assumptions, limitations, and analytical findings to technical and nontechnical stakeholders.

Take ownership of technical projects, proactively identify opportunities for improvement, and deliver scalable solutions.

Skills

Requirements

6+ years of experience in analytics engineering, data engineering, business intelligence engineering, or a related data-focused role.

Demonstrated experience supporting data and analytics for an e-commerce, retail, or consumer-focused business.

Advanced SQL skills and strong experience building production-grade data models and transformation pipelines.

Strong experience with dbt or a comparable data-transformation framework.

Proficiency in Python for data processing, automation, API integrations, and analytical workflows.

Hands-on experience with a cloud data warehouse such as Snowflake, BigQuery, Amazon Redshift, or Databricks.

Experience integrating and managing data from multiple platforms, retailer partners, APIs, third-party connectors, and structured files.

Experience with analytics and visualization tools such as Looker, Tableau, Power BI, Mode, Hex, or similar platforms.

Working knowledge of Git-based version control and collaborative development practices.

Strong commercial judgment and the ability to translate ambiguous business questions into clear technical requirements.

Excellent communication skills, including the ability to explain data logic and technical concepts to nontechnical stakeholders.

Strong documentation habits and exceptional attention to data accuracy, consistency, and detail.

A proactive, resourceful mindset with the ability to independently manage priorities and deliver results in a fast-paced environment.

Experience working with Shopify, retailer data feeds, marketing and attribution platforms, or omnichannel commerce systems.