Data Engineer - Sweed

About Sweed

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’ve been on the market for 7 years, continuously growing and refining our product. Our total team size is over 200 people. The development team is distributed globally and organized into cross-functional product teams (8–12 members), while our CEO, account managers, and customer success team are based in the USA.

Why This Role Matters

Our customers rely on accurate, timely, and trustworthy data to run their businesses. 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.

Responsibilities

• Design, build, and maintain data pipelines using Airflow and Trino to ingest and process data from multiple systems (databases, APIs, event streams, third-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 environment.
• Collaborate with cross-functional teams: Work closely with Product Analytics, Data Architecture, and Engineering teams to define and deliver data requirements.
• Optimize performance and cost: Fine-tune queries, pipelines, and storage for speed and efficiency.

Requirements

• 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.
• Hands-on experience with 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).
• Proactivity, critical thinking, and adaptability.

Nice-to-Have

• Infrastructure as Code (IaC): Terraform and Terragrunt for cloud deployments.
• IaC: Helm, Kustomize, and ArgoCD for Kubernetes deployments.
• Experience building and owning cloud infrastructure.

What We Offer

• Compensation: Salary in USD (B2B contract with the US company)
• Work Setup: 100% remote (core team hours: 09:00–15:00 GMT, flexible per team)
• Time Off: 20 paid vacation days, 12 holidays, and 3 sick days per year
• Healthcare: Medical insurance after probation period
• Equipment: Reimbursement for laptops, monitors, and work gear

Hiring Process

1. Recruiter Call (45 minutes, includes short English check)
2. Live-coding session (1 hour)
3. System Design interview (1 hour)
4. Final Interview (up to 45 minutes)