Analytics Engineer

Position Overview

• Location Type: Remote
• Job Type: Full-Time
• Salary: Not specified

SweedPos, a product-driven startup, is seeking an Analytics Engineer to join their team. The company is building an all-in-one cannabis retail platform and needs an individual to develop high-quality, scalable, and trusted data models for client-facing and internal analytics.

About SweedPos

Sweed reimagines cannabis retail operations with an enterprise-grade platform that integrates POS, eCommerce, Marketing, Analytics, and Inventory Management into a single solution. They focus on simplicity, efficiency, and innovation, building for scalability and performance to improve business growth for cannabis retailers.

Company Mission

Sweed believes in the medicinal potential of cannabis and aims to drive the industry's transformation by making cannabis retail more efficient, accessible, and customer-friendly.

Company Status

Operating for 7 years, SweedPos has a growing product and a strong focus on earning customer trust through continuous improvement and feature rollouts, while navigating the complex legal landscape of the cannabis industry.

Team Structure

The company has approximately 210 employees.

• The development team is globally distributed and organized into cross-functional product teams (8-12 members each), including front-end/back-end developers, QA specialists, and analysts, led by a Team Lead and Product Owner.
• The CEO, account managers, and customer success team are based in the USA.

Why This Role Matters

Cannabis retailers depend on data for daily business decisions. This role directly impacts those decisions by providing clean, performant, and well-governed data models. The Analytics Engineer will transform raw data into reliable reporting layers, collaborating with the Data Architect, engineers, product analysts, and clients. Key responsibilities include enforcing data quality through testing and validation.

Responsibilities

• Build and maintain analytics data models using dbt, focusing on structure, documentation, and maintainability.
• Implement data quality tests and validation logic to ensure accuracy and trust in reporting layers.
• Collaborate with the Data Architect on consistent modeling standards and architecture evolution.
• Work with internal teams and clients to clarify requirements and align on metric logic.
• Translate business needs into robust, reusable data models.
• Ensure the integrity of client-facing reports (reliability, freshness, metric correctness).
• Contribute to clear documentation, metric definitions, and data contracts.
• Support the continuous improvement of the data stack: dbt, ClickHouse, Snowflake, Dagster, Airbyte.

Requirements

• 2+ years of experience in analytics engineering, data engineering, or BI development.
• Strong SQL skills and hands-on experience with dbt.
• Solid understanding of data modeling for analytics/reporting (fact/dimension design).
• Experience writing and maintaining data quality tests (e.g., dbt tests, custom SQL assertions, test coverage frameworks).
• Experience with modern cloud-based data warehouses (e.g., Snowflake, ClickHouse, Redshift, BigQuery).
• Excellent spoken and written English for communication with internal teams and external clients.