Senior Data Engineer ID82547
AgileEngine
AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
We are looking for a Senior Data 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 AND BENEFITS
- 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
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