Senior Analytics Engineer – Data Applications

Job Description

Primary Function of Position

We are seeking a Senior Data Analytics & Full Stack Engineer to design and develop interactive, data-driven applications using open-source Python frameworks (such as Plotly Dash, Panel, or FastAPI-based web applications), integrated with modern data platforms such as Snowflake and dbt. This role combines deep expertise in analytics engineering with full-stack Python development to deliver scalable, self-service data solutions that support operations, planning, and decision-making.

The ideal candidate will partner closely with data analysts, data scientists, and business stakeholders to simplify access to insights, improve data quality, and drive automation. This role requires strong experience working within supply chain and operations domains, enabling the development of impactful solutions across planning, logistics, and manufacturing functions.

Essential Job Duties

Data Engineering & Analytics

• Design, build, and maintain scalable data pipelines using Python, dbt, Airflow, and/or Spark
• Develop curated, version-controlled datasets with well-defined metrics and business logic
• Ensure high data quality through testing frameworks, monitoring, and anomaly detection
• Optimize performance of data models and queries within cloud data platforms (Snowflake preferred)

Application Development

• Design and develop user-centric, interactive web applications using open-source frameworks such as Plotly Dash, Panel, or FastAPI-based front ends for data exploration, reporting, and workflow automation
• Build modular, reusable components for visualizations, data input/editing, approval workflows, and predictive use cases
• Deliver scalable and maintainable full-stack solutions leveraging Python frameworks (FastAPI, Flask)

Integration & Platform

• Integrate applications with Snowflake, S3, Smartsheet, and REST APIs to enable end-to-end data workflows
• Support CI/CD pipelines, version control, and containerized deployments (Docker)

Collaboration & Leadership

• Partner with stakeholders across supply chain, operations, and analytics teams to translate business requirements into technical solutions
• Collaborate with Enterprise Analytics teams to ensure alignment with data governance, security, and compliance standards
• Lead design decisions and promote engineering best practices across data and application development
• Mentor junior engineers and contribute to a culture of continuous improvement
• Document systems, processes, and methodologies for broader organizational use

Operational Expectations

• Maintain overlapping working hours with PST mornings for collaboration with global teams and stakeholders

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