About the role

We are looking for an Analytics Engineer to partner with an internal data team on a Customer Data Platform initiative, building Snowflake semantic structures, cleaning and transforming customer and behavioral datasets, and developing AI-readiness data models for a growing retail brand. You will write production-grade SQL and Python, build and maintain data models and semantic views in Snowflake, collaborate directly with cross-functional business stakeholders to translate operational needs into technical specifications, and maintain rigorous technical documentation across all built assets. Eastern Time Zone overlap preferred.

What you will do

• CDP Data Modeling (Primary Focus): Partner with an internal data team member to clean, transform, and structure incoming customer, sales, and behavioral datasets inside Snowflake to feed the Customer Data Platform.
• AI Readiness & Semantic Layer: Assist in developing Snowflake views, semantic models, and structured metadata to ground downstream AI agents and BI tools (Sigma).
• Ad-Hoc Operational Data Prep: Work with cross-functional stakeholders to engineer datasets for key retail initiatives (e.g., store inventory/RFID data projects, customer analytics).
• Write production-grade, performant SQL queries and Python scripts for data transformation, extraction, and automated data wrangling.
• Partner directly with business stakeholders to translate ambiguous business requests into clean, structured data models.
• Parse and flatten complex semi-structured data (JSON, nested payloads) landed from cloud sources.
• Build and maintain data models and semantic views in Snowflake.
• Write thorough data dictionaries, model descriptions, and documentation for built assets.
• Maintain clean code repositories and follow git workflows and data testing protocols.
• Take on additional analytics engineering priorities as assigned, based on evolving business needs.

Must haves

• 4+ years writing complex, optimized SQL — window functions, and handling semi-structured/nested data formats.
• Strong Python: Proficient writing clean, modular Python scripts for data manipulation, automation, API/file processing, and data quality checks.
• Cloud Platform Experience: Hands-on experience working within at least one major cloud data ecosystem (AWS, Snowflake, GCP, or Azure).
• Strong Stakeholder Communication: Ability to collaborate directly with business partners, ask clarifying questions, and turn operational needs into technical specifications.
• Rigorous Documentation Focus: A disciplined habit of maintaining thorough technical documentation and code comments.
• Upper-intermediate English level.

Nice to haves

• dbt (Data Build Tool): Experience writing, modularizing, and testing dbt models.
• Snowflake & AWS S3: Direct experience querying Snowflake data warehouses and manipulating staging data stored in S3 buckets.
• Orchestration Tools: Familiarity with Apache Airflow or similar pipeline schedulers.
• Retail / E-Commerce Knowledge: Background in omni-channel retail, store operations, inventory management, or customer analytics.

Perks

• Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
• Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
• Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
• Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
• Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
• Well-being & support: access local well-being programs and people-focused support tailored to your location

Have any questions?