Senior Python Engineer - ML and Data Science
ClickhouseFull Time
Senior (5 to 8 years), Expert & Leadership (9+ years)
Candidates should have experience in Python for data processing, a strong understanding of batch and real-time data processing, and proficiency with Git, CI/CD systems, and cloud platforms. Expertise in pipeline orchestration frameworks like Airflow or Dagster, strong SQL skills for complex queries and data manipulation, and experience designing and optimizing queries and data storage structures in ClickHouse with large datasets are essential. Experience with C# is a plus, and knowledge of Docker, Kubernetes, and Helm charts is highly desirable. Upper-Intermediate English proficiency is required for team communication and documentation.
The Data Engineer will migrate the current reporting infrastructure to a new data platform using Airbyte, dbt, Dagster, ClickHouse, and Cube. Responsibilities include setting up data export pipelines for clients, implementing data streams for ML workflows, and establishing pipeline monitoring and alerting systems. The role also involves setting up and managing ingestion pipelines, integrating various data sources, creating and optimizing data transformation models with dbt, writing data quality tests, and managing data pipelines with automated schedules and error handling.
Retail cannabis point-of-sale and management solution
Sweed offers a complete solution for retail cannabis businesses by combining point-of-sale systems with e-commerce, delivery, analytics, marketing, and inventory management features. This integrated approach simplifies operations for cannabis retailers, allowing them to manage all aspects of their business from a single platform. Unlike competitors that may require multiple separate systems, Sweed provides an all-in-one service that enhances efficiency and customer interaction. The company operates on a subscription model, ensuring a steady revenue stream while helping retailers improve their sales processes and make informed decisions based on data insights.