Hi there!
We’re Sweed, a product-driven company building an all-in-one cannabis retail platform. We’re looking for an Analytics / Data Engineer to help us build reliable, scalable, and trusted data models that power both client-facing and internal analytics.
At Sweed, we’re reimagining how cannabis retailers operate. Our enterprise-grade platform combines POS, eCommerce, Marketing, Analytics, and Inventory Management into one seamless solution - helping retailers replace multiple disconnected tools with a unified operating system.
We’ve been on the market for 7+ years and continue to grow, refine our product, and support cannabis retailers in a complex and highly regulated industry.
We’re currently migrating our analytics and reporting ecosystem from several legacy systems to a new modern data platform.
This is not a pure BI or dashboard-building role. The main focus is on building reliable data marts, migrating reporting logic, improving data quality, and helping us mature our analytics engineering practices.
You’ll work closely with our Data Architect, Analytics Engineers, Data Engineers, and Client Reporting team. The role sits between analytics and data engineering: we need someone who can understand business requirements, but also think technically about pipelines, partitioning, query performance, modeling, and reconciliation.
Our current landscape includes several legacy layers built around ClickHouse and Snowflake. We’re now moving toward a more scalable modern data stack centered around dbt + Trino.
ClickHouse is still heavily involved in the legacy environment, so experience with ClickHouse - especially around migration, optimization, and reconciliation - would be a strong plus.
The environment is still evolving. Some parts of CI/CD, testing, documentation, and data quality processes are already in place, while others are actively being built and improved.
You’ll join the Data Layer team, which currently includes:
Data Architect / Team Lead
3 internal Analytics Engineers
1 external contractor
close collaboration with the DWH / Data Engineering team
regular interaction with the Client Reporting team as the main internal stakeholder
The DWH team owns ingestion, replication, source systems, and infrastructure. The Data Layer team owns the transformation and analytical layer after the data lands: dbt models, marts, reporting logic, reconciliation, documentation, and data contracts.
Build and maintain analytics data models using dbt - incremental pipelines (merge strategies, hashdiff, SCD Type 1/2) across retail domains (sales, inventory, loyalty, marketing, promotions), with strong emphasis on structure, documentation, and maintainability
Implement data quality tests and validation logic, ensuring accuracy and trust across reporting layers
Own conformed dimensions as shared contracts across downstream consumers
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, Trino, ClickHouse, Airflow,http://cube.devCube.dev, Metabase
5+ years of experience in analytics engineering, data engineering, BI development, or similar data-focused roles
Strong SQL skills
Hands-on experience with dbt
Solid understanding of analytical data modeling: facts, dimensions, grains, SCD patterns, data marts
Understanding of ETL/ELT pipelines and reporting layers
Experience with query optimization, partitioning, incremental models, and data pipeline reliability
Experience with data reconciliation and investigating inconsistent metrics
Ability to work with business requirements and ask strong clarifying questions
Good written and spoken English
Strong ownership mindset and ability to work autonomously in a fast-changing environment
Willingness to learn, adapt, and dive deeper into technical details
Trino / Presto experience
ClickHouse experience
Airflow experience
Experience with Metabase, Superset, Cube.dev, Looker, Tableau, or similar BI / semantic layer tools
Experience with data contracts
Experience with retail, marketplace, eCommerce, fintech, payments, or transactional data
Experience in migration projects
Experience working in distributed / remote teams
This role is best suited for someone who enjoys the middle ground between analytics and engineering.
You probably won’t enjoy this role if you only want to build dashboards or only want to work on pure infrastructure. We need someone who can take a requirement, understand the business logic behind it, design the model, implement it in dbt, validate the result, and ensure the reporting layer can actually be trusted.
The environment is still evolving, so we value people who are comfortable with ambiguity, changing priorities, and imperfect processes.
Salary in USD
B2B contract with a US company
100% remote setup
Flexible working hours
Core collaboration time: 09:00–15:00 GMT
20 paid vacation days per year
12 holidays per year
3 sick leave days
Medical insurance after probation
Equipment reimbursement
Recruiter Call — up to 45 minutes
Technical Interview — up to 1.5 hours (SQL, dbt, modeling, reconciliation, and data quality logic)
Final Interview — up to 30 minutes