Job description:

Objective
Our team is seeking a versatile and seasoned Data Science Engineering professional with specialized
expertise in data warehousing and extensive experience with Django and React. The ideal candidate will be
adept at handling a wide array of tasks including front-end development, back-end development, data
science, DevOps, and enterprise architecture. The contractor will play a critical role in developing high performance data solutions, enhancing our business intelligence and analytics capabilities, and supporting
various other technical needs across our organization.
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Core Responsibilities
Architect and manage data warehousing solutions, with a focus on Snowflake and other leading platforms.
Build and optimize data pipelines, ensuring efficient data flow and storage that aligns with business
requirements.
Develop front-end interfaces with ReactJS and back-end services with Django RESTPython.
Create and deploy sophisticated machine learning models on cloud platforms (GCP or Azure ML services).
Produce high-quality code that is scalable, readable, and adheres to industry best practice.
Required Qualifications
Master s degree in computer science, Data Science, Computer Engineering, or a related field.
At least 5 years of experience in software development and data engineering, with a proven track record in
software development.
Advanced skills in JavaScript, and Python, and familiarity with modern programming frameworks and
technologies.
In-depth knowledge of Snowflake, data lakes, and other data warehousing technologies.
Expertise in developing and maintaining RESTful APIs and web service integration.
Solid understanding of DockerKubernetes for deployment, and databases (Postgres, MySQL).
Preferred Qualifications
Ability to work autonomously, efficiently, and accurately in a dynamic, fast-paced environment.
Excellent problem-solving skills with a keen analytical mindset suitable for tackling complex data challenges.
Demonstrated experience in architecting full-stack applications for Business Intelligence (BI) insights in an
enterprise environment, emphasizing the integration of front-end analytics platforms with back-end data
warehousing and processing technologies to drive data-driven decision-making.
Business domain knowledge in networking is a significant plus, especially given our focus on observability