Data Engineer
SweedHi there!
We're SweedPos, a product-driven startup building an all-in-one cannabis retail platform. We’re looking for an Data 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
Our total team size is over 200 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 accurate, timely, and trustworthy data to run their business. From sales analytics to inventory tracking and operational reporting, our data pipelines are mission-critical.
As a Data Engineer, you’ll be at the center of our data ecosystem: ensuring that data flows from our product, integrations, and third-party systems into our analytics and operational platforms with speed, accuracy, and reliability. Your work will enable analysts, product teams, and leadership to make better decisions — and will directly impact the features our customers use every day.
What to do in the project?
Design, build, and maintain data pipelines using Airbyte, Debezium, and Dagster to ingest and process data from multiple systems (databases, APIs, event streams, 3rd-party integrations).
Develop and maintain ELT workflows with dbt, ensuring modular, scalable, and well-documented data transformations.
Manage and optimize our data warehouses — ClickHouse for high-performance analytics and Snowflake for scalable, multi-use workloads.
Improve data quality and reliability — implement monitoring, validation, and alerting for pipelines to ensure accuracy and consistency.
Collaborate with cross-functional teams — work closely with Product Analytics, Data Architecture, and Engineering teams to define data requirements and deliver them effectively.
Support instrumentation efforts — design and implement event tracking for new product features in collaboration with engineering teams.
Optimize performance and cost — fine-tune queries, pipelines, and storage for speed and efficiency.
Document data assets — maintain clear documentation for data sources, pipelines, and models.
What professional skills are important for us?
3+ years of experience in data engineering or a related field.
Strong proficiency in SQL and Python.
Proven hands-on experience with:
Airbyte for data ingestion.
Debezium for CDC (Change Data Capture) pipelines.
Dagster (or similar orchestrators like Airflow) for workflow management.
dbt for data transformations and modeling.
ClickHouse and Snowflake for analytics workloads.
Solid understanding of data modeling (star schema, snowflake schema, dimensional modeling).
Familiarity with event-based data architectures and real-time processing.
Strong communication skills — able to collaborate with technical and non-technical stakeholders.
Bonus: experience in B2B SaaS or regulated markets (fintech, healthcare, cannabis).
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
Recruiter Call (up to 45 min) – Intro & expectations.
Hiring Manager Call (up to 45 min) – Deep dive into your data engineering experience.
Technical Interview (up to 1.5 hrs) – Data architecture & engineering problem-solving.
Final Interview (up to 1 hr) – Conversation with CTO, Data Lead, or other leadership.