Data Engineer

Genetica is a Venture Capital backed start up in the Cannabis space. Retail is challenging even when everything is “going right.” Add in the complexities of cannabis where retailers face onerous regulations, fickle customers, and tight margins, it’s no wonder companies are struggling. Dispensaries are constantly looking for ways to attract and retain new customers so they can increase profits. But nobody is approaching it the right way. They are piecing together different tools and strategies instead of using their data to understand their customers, their employees, and their business. Insert Genetica. Genetica provides AI software that makes all data work for retailers, their customers, their employees and their stores.

We are seeking a skilled Data Engineer to join our data team. The ideal candidate will have a comprehensive background in Python, SQL, data quality tools, data cleaning libraries like pandas, data validation frameworks, relational databases, big data tools, data integration tools and frameworks, and cloud platforms, particularly AWS. This role is pivotal in optimizing our data architecture, streamlining data processing, and ensuring data is readily available for various analytical and operational needs.

Key Responsibilities:

Design, construct, install, and maintain large-scale processing systems and other infrastructure.
Build and maintain scalable ETL pipelines using Python and relevant data integration tools.
Collaborate with data scientists, analysts, and other stakeholders to ensure data availability, quality, and consistency.
Optimize and improve the performance of existing data systems using SQL and data quality tools.
Work closely with data architecture and modeling teams to design and implement scalable database structures.
Ensure data security and compliance with relevant regulations.
Monitor data processing systems to identify and resolve issues.
Stay updated with emerging technologies in data engineering and introduce them as needed.
Collaborate with other teams to better integrate systems and data.
Document and maintain architectural specifications, data engineering processes, and best practices.

Qualifications:

Bachelor’s degree in Computer Science, Engineering, or a related field.
Proven experience as a Data Engineer or in a similar role.
Comprehensive knowledge of Python, SQL, data quality tools, data cleaning libraries like pandas, data validation frameworks, relational databases, and big data tools.
Experience with data integration tools and frameworks.
Strong problem-solving skills and analytical thinking.
Excellent communication skills to collaborate with cross-functional teams.
Familiarity with cloud platforms, especially AWS.