Senior Analytics Engineer (Marketing Data)

POSITION

Senior Analytics Engineer (Marketing Data)

REQUIRED SKILLS

• • Approximately five or more years of relevant professional experience in analytics engineering, data engineering, marketing data, or a closely related role.
  • Professional, hands-on experience working with Google Analytics data in a business or production environment. Coursework, certifications, or self-directed learning without applied work experience are not sufficient.
  • Professional experience supporting data in a retail or ecommerce environment.
  • Advanced SQL skills and hands-on experience designing fit-for-purpose data models, transformations, and materializations in Snowflake.
  • Working proficiency in Python, including the ability to read, evaluate, troubleshoot, and improve code written by others.
  • Experience reviewing API documentation and mapping API objects, endpoints, fields, and identifiers to business requirements.
  • Experience with Git and version-controlled development practices, including code review, testing, and CI/CD.
  • Demonstrated ability to elicit requirements from stakeholders, bring structure to ambiguous or nonlinear discussions, and translate business needs into precise, actionable technical work.
  • Strong understanding of data validation across multiple stages of a data pipeline.
  • Ability to work independently, exercise sound technical judgment, and recognize when requirements or proposed solutions do not make sense.
  • Exceptional written and verbal communication skills in English.

• • Approximately five or more years of relevant professional experience in analytics engineering, data engineering, marketing data, or a closely related role.
  • Professional, hands-on experience working with Google Analytics data in a business or production environment. Coursework, certifications, or self-directed learning without applied work experience are not sufficient.
  • Professional experience supporting data in a retail or ecommerce environment.
  • Advanced SQL skills and hands-on experience designing fit-for-purpose data models, transformations, and materializations in Snowflake.
  • Working proficiency in Python, including the ability to read, evaluate, troubleshoot, and improve code written by others.
  • Experience reviewing API documentation and mapping API objects, endpoints, fields, and identifiers to business requirements.
  • Experience with Git and version-controlled development practices, including code review, testing, and CI/CD.
  • Demonstrated ability to elicit requirements from stakeholders, bring structure to ambiguous or nonlinear discussions, and translate business needs into precise, actionable technical work.
  • Strong understanding of data validation across multiple stages of a data pipeline.
  • Ability to work independently, exercise sound technical judgment, and recognize when requirements or proposed solutions do not make sense.
  • Exceptional written and verbal communication skills in English.

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

• • CDP implementation or ongoing CDP data enablement, customer 360 data models, identity resolution, or audience activation.
  • Event-level web behavioral data, cross-channel or cross-device identifiers, and marketing attribution data and concepts.
  • Anonymous-to-known identification, consent and privacy requirements, and audience eligibility or suppression logic.
  • Google Ads, Meta Ads, email, SMS, loyalty, or other paid-media and marketing technology platforms.
  • Building or maintaining API-based ingestion processes.
  • Avoid
    • People who don't have practical application of technical requirements
    • People who can't work independently or with stakeholders with strong opinions