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Sweedpos.com

Data Engineer

  • Seen live on Sweedpos.com's site 4 days ago
  • Mid level
  • Remote
Pay
Not stated
Location
Remote International
Open for
12+ days
First seen
Oct 23, 2026

Posting record

No flags

Open 12+ days

The posting's record, oldest first
  1. Sweedpos.com's site dates the posting
  2. Ghostless first sees this listing
  3. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Sweedpos.com, so its true age is longer.

Last checked Oct 31, 2026.

How well do you match?

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What it asks of you

3+ years of experience
“3+ years of experience in data engineering or a related field.” (quoted from the posting)

What the posting discloses

Not stated: Pay, real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Some employers add pay only on their own site. Check the original posting before you rule it out.

Skills mentioned

About the role

Hi there!

We're SweedPos , a product-driven startup building an all-in-one cannabis retail platform. We’re on the lookout for a Data Engineer to join us remotely and help us scale and optimize our platform.

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 Airflow , and Trino to ingest and process data from multiple systems (databases, APIs, event streams, 3rd-party integrations).
  • Improve observability — implement monitoring, validation, and alerting for pipelines to ensure accuracy and consistency.
  • Develop and maintain the platform — deploy, monitor and maintain services in our aws cloud
  • Collaborate with cross-functional teams — work closely with Product Analytics, Data Architecture, and Engineering teams to define data requirements and deliver them effectively.
  • Optimize performance and cost — fine-tune queries, pipelines, and storage for speed and efficiency.

What professional skills are important to us?

  • 3+ years of experience in data engineering or a related field.
  • Strong proficiency in SQL and Python .
  • Hands-on experience with:
  • Airflow for workflow management
  • OLAP databases, distributed query engines and data processing frameworks ( clickhouse , trino , spark etc) for analytical workloads
  • Solid understanding of data modeling and data engineering best practices
  • Familiarity with event-based data architectures and streaming ( spark , flink )
  • Bonus points for:
  • IaC: terraform , terragrunt for cloud infrastructure deployments
  • IaC: helm , kustomize , argocd for k8s deployments
  • Experience with building and owning cloud infrastructure

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

  • Compensation in USD (B2B independent contractor agreement with a US-based company)
  • 100% remote – We’re a remote-first company, no offices needed!
  • Flexible working hours – Core team time: 10:00-16:00 CET (flexible per team)
  • 20 paid time off days per year
  • 12 holidays per year
  • 3 paid sick days
  • Medical insurance after the first 3 months of collaboration
  • Equipment reimbursement (laptops, monitors, etc.)

Hiring Process

  • Recruiter Call (45 minutes) – Includes a short English check
  • Live-coding session (1 hour)
  • System Design (1 hour)
  • Final Interview (up to 45 minutes)

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