Analytics Engineer

Hi there!

We're SweedPos, a product-driven startup building an all-in-one cannabis retail platform. We’re looking for an Analytics Engineer to help us deliver high-quality, scalable, and trusted data models that power both client-facing and internal analytics. Fully remote.

About Us

At Sweed, we’re reimagining how cannabis retailers operate. Our enterprise-grade platform combines POS, eCommerce, Marketing, Analytics and Inventory Management into a single, seamless solution—eliminating the need for multiple third-party tools.

We believe in simplicity, efficiency, and innovation. That’s why we build for scalability and performance, making life easier for cannabis retailers while driving real business growth.

Why We’re Doing This

At Sweed, we believe in the medicinal potential of cannabis. It has been shown to help with chronic pain, anxiety, depression, and many other conditions. Despite the lingering stigma, we see cannabis as a powerful tool for improving lives.

The industry is evolving rapidly, and we’re here to drive that transformation—making cannabis retail more efficient, accessible, and customer-friendly.

Where We Are Now

We’ve been on the market for 7 years, continuously growing and refining our product.

Our focus is on earning customer trust, which means constantly improving our delivery processes and rolling out new features. At the same time, we navigate the complex legal landscape of the cannabis industry, ensuring our platform remains compliant and future-proof.

Team Structure

Right now, our total team size is around 210 people:

The development team is distributed globally and organized into cross-functional product teams. These teams typically consist of 8–12 members, including front-end and back-end developers, QA specialists, and analysts.
Each team is led by a Team Lead and a Product Owner, ensuring effective collaboration and clear direction.
Meanwhile, our CEO, account managers, and customer success team are based in the USA, working closely with us to align product development with business and user needs.

Why This Role Matters

Our customers - cannabis retailers - rely on data to make daily business decisions. As an Analytics Engineer, your work will directly power these decisions via clean, performant, and well-governed data models.

You’ll be responsible for transforming raw data into reliable reporting layers — working closely with our Data Architect, engineers, product analysts, and sometimes even clients. You’ll also play a key role in enforcing data quality through testing and validation practices.

What to do in the project?

• Build and maintain analytics data models using dbt - with a strong emphasis on structure, documentation, and maintainability

• Implement data quality tests and validation logic, ensuring accuracy and trust across reporting layers

• Collaborate with the Data Architect to apply consistent modeling standards and support architecture evolution

• Work with internal teams and sometimes clients to clarify requirements and align on metric logic

• Translate business needs into robust, reusable data models

• Ensure the integrity of client-facing reports, including reliability, freshness, and metric correctness

• Contribute to clear documentation, metric definitions, and data contracts

• Support the continuous improvement of our modern data stack: dbt, ClickHouse, Snowflake, Dagster, Airbyte

What professional skills are important for us?

• 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, including 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 — you’ll communicate with internal teams and sometimes with external clients

• Ability to clearly explain data logic and metric definitions to non-technical stakeholders

• Meticulous approach to documentation, testing, and ownership of data artifacts

• Bonus: experience supporting client-facing dashboards or embedded analytics

What Else Matters?

• Proactivity – We love team members who take initiative and provide feedback

• Critical thinking – We value problem-solvers who think beyond just writing code

• Adaptability – Our industry is evolving fast, and we need people who thrive in change

What We Offer

• Salary in USD (B2B contract with the US company)

• 100% remote – We’re a remote-first company, no offices needed!

• Flexible working hours – Core team time: 09:00-15:00 GMT (flexible per team)

• 20 paid vacation days per year

• 12 holidays per year

• 3 sick leave days

• Medical insurance after probation

• Equipment reimbursement (laptops, monitors, etc.)

Hiring Process

1. Recruiter Call (up to 45 minutes) – Intro & expectations

2. Hiring Manage Call (up to 45 minutes) - Deep dive into your Data background

3. Technical Interview (up to 1.5 hours) – SQL, dbt, data modeling, and DQ test logic

4. Final Interview (up to 1 hour) – Chat with Data Architect and Product stakeholders