Senior Python Engineer - ML and Data Science
ClickhouseFull Time
Senior (5 to 8 years), Expert & Leadership (9+ years)
Candidates must possess 5+ years of professional software development experience with Python, a strong understanding of software engineering best practices, experience building and optimizing ETL/ELT processes and data pipelines, proficiency with SQL and database concepts, experience with data processing frameworks such as Pandas, an understanding of software design patterns and architectural principles, the ability to write clean, well-documented, and maintainable code, experience with unit testing and test automation, experience working with any cloud provider (GCP is preferred), experience with CI/CD pipelines and Infrastructure as code, experience with Containerization technologies like Docker or Kubernetes, and a Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience).
The Data Engineer will develop and maintain data pipelines and ETL/ELT processes using Python, design and implement scalable, high-performance applications, work collaboratively with cross-functional teams to define requirements and deliver solutions, develop and manage near real-time data streaming solutions using Pub/Sub or Beam, contribute to code reviews, architecture discussions, and continuous improvement initiatives, monitor and troubleshoot production systems to ensure reliability and performance, and write clean, well-documented, and maintainable code.
Data-driven decision-making solutions for organizations
ShyftLabs helps organizations adopt a data-first approach to their decision-making processes. Their services focus on establishing systems that enable companies to make quicker and more informed decisions based on data analysis. This approach allows businesses to gain insights that can keep them ahead of their competitors. Unlike other companies that may offer generic consulting services, ShyftLabs emphasizes the importance of data in driving decisions, ensuring that organizations can leverage their data effectively to enhance their strategic planning and operational efficiency.