Data Engineer

We are a young and innovative software company, looking to dramatically change how pharma, biotech, and medical device companies manage their quality and compliance regulated processes by leveraging Generative AI capabilities.

Dot Compliance provides to companies both large and small, worldwide, a ready-to-deploy, Salesforce-native eQMS with the industry’s first AI solution specifically built to deliver safe, reliable decision guidance for critical quality issues. This offers faster, more proactive quality and compliance through Vertical AI that empowers data-driven decision making in life sciences quality and compliance.

Responsibilities:

We are looking for a highly motivated and talented Data Engineer to join our Data Science team, reporting directly to the company’s Chief Data Scientist. As a Data Engineer, you will take a major part in the design, development, implementation and maintenance of our AI Data Pipeline built on AWS. You will be building the data pipeline infrastructure and associated AI Agents as well as developing scripts, tools, and dashboards for manipulating, analyzing, organizing and visualizing our data. Our ideal candidate is a versatile, organized, team-player, who enjoys tinkering with data technologies, engineering and cloud, and is always on the lookout for an opportunity to optimize.

Requirements:

• Bachelor's degree in computer science or related field
• 2+ years of experience in software development in Data Engineering and in building data pipelines
• 2+ years of programming experience with Python
• 2+ years of experience with SQL and no-SQL databases
• 2+ years of experience with AWS (or other cloud platforms)
• Linux and DevOps skills
• Strong skills in data manipulation, cleanup, management, organization, visualization and storage. Ability to write custom tools and integrate with existing tools and frameworks
• Experience with data pipeline development, testing and monitoring
• Strong analytical and problem-solving abilities to troubleshoot data-related issues, optimize queries, and improve data pipelines' performance.
• Familiarity with serverless architecture - a plus
• Familiarity with machine learning frameworks in Python, such as: pandas, numpy, sklearn, pytorch, .. - a plus