Hi there!
Data Quality Engineer
Further - more, in the Q&A.
What are we doing?
At Sweed, we offer a comprehensive cannabis retail solution with a wide range of features, including powerful POS functionality, in-depth analytics, marketing and promotional tools, efficient inventory management, and more. Our progressive web app can be easily accessed through the tablets already available in your store without any additional hardware required.
Since our establishment, we have been committed to creating an all-in-one system tailored to the specific needs of large cannabis retailers. Today, we are proud to be a market leader, owing much of our success to our signature killer feature – providing a full spectrum of software in one solution.
Why are we doing this?
At our company, we are driven by our passion for the medicinal potential of plants. Cannabis possesses unique properties that can help alleviate chronic pain, anxiety, depression, epilepsy, multiple sclerosis, glaucoma, and sleep disorders.
Although a significant amount of stigma is associated with this area, we firmly believe these plants possess unique properties and have helped countless people improve their quality of life. This rapidly growing industry presents immense potential for career advancement and personal fulfillment, and we are excited to explore how we can contribute to this dynamic field.
How old is the project? What stage is it at?
The product is already 4 years on the market and in the active development stage.
Our current priority is establishing and maintaining strong customer trust, which has driven the development of our delivery processes that allow us to launch new features daily. Given the highly specialized nature of the cannabis retail market, we are committed to rapidly meeting the evolving needs of our customers. Furthermore, the market's unique legal framework presents challenges with significant variations in state-level taxes, delivery regulations, and other factors.
Who are we looking for?
We’re looking for a Data Quality Engineer to join our Data team. This position offers an opportunity to apply your expertise in data validation, develop automated solutions, and refine our processes to maintain the high standards of data quality.
As part of this role, you’ll work on critical initiatives such as a cross-validation project aimed at automating the process of ensuring that metrics between different datasets are tied with each other.
What professional skills are important to us?
- 3+ years of experience as a Data Quality Engineer or in a similar position.
- Strong understanding of data quality concepts and methodologies.
- Expertise in automating data quality checks.
- Proficiency in SQL, Python, Pytest and Pandas.
3+ years of experience as a Data Quality Engineer or in a similar position.
Strong understanding of data quality concepts and methodologies.
Expertise in automating data quality checks.
Proficiency in SQL, Python, Pytest and Pandas.
Nice to have skills:
- Experience with orchestration systems such as Dagster or Airflow.
- Familiarity with Data Quality frameworks like dbt tests, Great Expectations, or Soda.
- Knowledge of metadata management tools such as Open Metadata.
- Experience with UI test automation.
Experience with orchestration systems such as Dagster or Airflow.
Familiarity with Data Quality frameworks like dbt tests, Great Expectations, or Soda.
Knowledge of metadata management tools such as Open Metadata.
Experience with UI test automation.
What to do in the project?
- Develop and implement robust solutions for automating data quality validation processes.
- Collaborate with a cross-functional team to design and align technical solutions that improve data quality.
- Optimize the performance of data pipelines and ensure alignment of metrics across datasets.
Develop and implement robust solutions for automating data quality validation processes.
Collaborate with a cross-functional team to design and align technical solutions that improve data quality.
Optimize the performance of data pipelines and ensure alignment of metrics across datasets.
Team size and structure?
We have structured our team around particular products. Typically, each team consists of 10-12 people, including front-end and back-end engineers, QA specialists, and analysts. A separate product owner is responsible for each team. Currently, we have a team of around 150 people.
The conditions:
Is there a probation period, and how long does it last?
What is the work schedule?
Is it possible to work remotely?
What currency is the salary paid in, and what is the form of employment?
The number of vacation days?
The number of sick leave days?
Social package (medical insurance, other):
The process:
1 hour
1.5 hour