Software Engineer Backend - Data Pipelines, ETL process, Python, SQL

Rate-£60 per hour (480 per day umbrella)

6 months contract

Flexibility to work in alignment with US working hours is required

Companies Data Science is building a Python library that enables data scientists and engineers to:

1. analyze experiments with state-of-art statistical inferencing built-in,
2. fetch data from up-to-date sources of truth,
3. build deeper insights on top of companies data, and
4. centralize, standardize, and socialize repeatable analyses and data science tasks.

We are just getting started and seek to expand the set of features in this library, improve performance and throughput, and develop a community of Snoo contributors. To realize this vision of a collaborative data science library, we are looking for a full-time Python developer with strong technical and interpersonal skills and a sense of ownership.

What’s in it for you?

• You will contribute to the flagship foundational project in the Data Science org, which has visibility all the way to the execs
• You will have the opportunity to wear the different hats of a developer, a tech lead, and a product manager. Driven by self initiative, you will be welcome to help define the long term roadmap and contribute as an equal partner in the development of this library and in ensuring its longevity
• You will be welcome to play a leading role in developing and nurturing a community of contributors in the Data Science Org
• You will have the opportunity to immerse in the domains of data science and machine learning, and uplevel the team in how we support our XFNs with high leverage, data driven insights

Skills and experience you must have.

• Object-oriented software development experience in Python
• Experience in writing production quality code
• Experience in CI/CD tooling
• Experience in Python testing
• Well grounded opinions on best practices, performance, and documentation
• Proven ability to take informed decisions to balance code performance, quality, and velocity
• Growth mindset as well as an ability to up-level their peers
• Some experience with Airflow, Bigquery SQL, and Python libraries like Pandas
• Hands on familiarity with data engineering, BQ Terraform

kills and experience which will be greatly appreciated.

• The above experience, but at Reddit
• Hands on experience with Airflow, Bigquery SQL, and Python libraries like Pandas, Ibis
• Experience in data engineering, BQ Terraform
• Familiarity with, or excitement to learn, data science/experimentation techniques
• Focus on end-users' contexts and needs