Senior Data Engineer (Retail Pricing & Operations)

Technical Skills:

Experience: 5+ years of hands-on data engineering experience, ideally in retail, CPG, e-commerce, or supply chain environments. Core Tech Stack: Expert proficiency in SQL, Python, dbt, Databricks Unity Catalog, and AWS data infrastructure. Automation & Version Control: Proven success building automated ingestion frameworks and utilizing GitHub for repository management and CI/CD pipelines. Data Modeling: Solid understanding of dimensional modeling, Star Schema, and building unified enterprise catalog spaces. Soft Skills: Excellent remote communication skills, proactive problem-solving mindset, and the ability to work independently in a nearshore setup. Proficiency in English: C1–C2Soft Skills:

• Creativity and innovation.
• Attention to detail.
• Accountability and ownership.
• Time management and prioritization.
• Adaptability in high-volume environments.

Projects

We are seeking a highly talented Senior Data Engineer to design, build, and maintain high-volume data architecture supporting critical retail pricing strategy and physical store space planning. Operating within our modern cloud ecosystem (Databricks on AWS), you will automate data pipelines connecting internal store management software with large external CPG vendor feeds (e.g., major beverage, packaged goods, and grocery suppliers) and market-matching datasets.

Responsibilities:

Pipeline Automation & Data Ingestion: Design, build, and optimize automated data feeds for external CPG vendor cost updates, competitor market pricing, and store spatial layout data. Modern Data Stack Governance: Manage and structure modular pipelines using dbt, Databricks Unity Catalog, and Python, ensuring high performance, proper data governance, and schema control. Complex Data Transformations: Write advanced, production-grade SQL and Python scripts to clean, structure, and stitch disparate vendor datasets into scalable data models. CI/CD & Code Quality: Enforce continuous integration, unit testing, version control, and automated deployment practices using GitHub. Cloud Architecture Optimization: Monitor and tune compute performance, data storage, and pipeline execution within AWS and Databricks.

Benefits:

• US holidays.
• 15 vacation days per year.
• Professional growth opportunities within the company.