Senior Analytics Engineer - Marketing Data - CDP (Retail industry background)

Project Description

We are looking for a Senior Analytics Engineer to design and build the data structures that support our customer data platform (CDP) and broader marketing data needs.

This is a hands-on technical role at the intersection of data engineering, data modeling, business analysis, and marketing technology. The person in this role will work directly with marketing and technical stakeholders to understand business use cases, determine what data is available from upstream platforms, and translate those findings into actionable requirements and reliable Snowflake data solutions.

Initially, this role will focus primarily on our CDP implementation. The Senior Analytics Engineer will identify and build the models and materializations needed to support CDP use cases, audience activation, customer insights, and related downstream processes. Over time, the role will expand to support the broader data needs of our Marketing Analytics team.

This is not primarily a dashboard or visualization development role. Success requires the ability to understand complex marketing data, impose structure on ambiguous or rapidly evolving requirements, and build fit-for-purpose datasets for downstream consumers.

• The role is more focused on data preparation and data quality upstream of the CDP.
• Candidate needs to develop a strong working understanding of the data, what needs to feed the CDP, and the requirements/use cases that data needs to support.
• Looking for someone with the technical judgment to understand whether the available data can actually support the requested business use case.

What We’re Looking For

The right candidate combines technical depth with strong analytical judgment. They can move comfortably between a stakeholder conversation, API documentation, raw source data, a Jira ticket, and production-quality Snowflake code.

They do not treat a stakeholder’s initial request as a complete technical specification. They investigate the intended outcome, determine what the source data can realistically support, identify missing decisions or dependencies, and turn the result into work that engineers and business partners can act upon.

They are equally comfortable building a solution themselves and serving as a technically knowledgeable internal customer for work built by another data engineer.

• Advanced Snowflake and SQL
• Strong Python experience but will not be doing heavy daily Python coding
• Should be able to read and understand code, debug and troubleshoot existing code
• Some AI-assisted development, using Claude internally
• Not just chatting with AI or vibe coding but applying it to workflows
• Google Analytics
• No expert on the team, need to know enough and have some applied experience, investigate and dive into API documentation, weeding through and discerning what works or doesn’t
• Experience and exposure to upstream data into a CDP
• Strong emphasis on understanding and validating data quality upstream of the CDP.
• Not heavily ingesting data (might have to sometimes) but need to understand how it works
• Strong communication and ability to interface with stakeholders
• Be an influencer, advocate for what's possible and not, while escalating as needed
• Self starters, problem solvers, independent workers