Principal Data Engineer: Platform Reliability & Automation

Principal Data Engineer: Platform Reliability & Automation

Full-Time 80000 - 100000 £ / year (est.) No working from home possible
Harrington Starr

At a Glance

  • Tasks: Lead the design of CI/CD frameworks and enhance platform reliability through automation.
  • Company: Harrington Starr, a forward-thinking company focused on cloud data solutions.
  • Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
  • Other info: A leadership role with significant impact on data product operations.
  • Why this job: Join a dynamic team to innovate and scale engineering practices in a modern environment.
  • Qualifications: Expertise in Python, SQL, and experience with cloud platforms required.

The predicted salary is between 80000 - 100000 £ per year.

Harrington Starr is seeking a Principal Data Engineer to innovate and scale engineering practices on a modern cloud data platform. This leadership role emphasizes platform reliability, automation, and data product operations.

Key responsibilities include:

  • Designing CI/CD frameworks
  • Driving operational excellence
  • Implementing automation practices

Ideal candidates will have strong expertise in Python and SQL, experience with cloud platforms, and a commitment to software engineering best practices.

Principal Data Engineer: Platform Reliability & Automation employer: Harrington Starr

Harrington Starr is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for a Principal Data Engineer to thrive. With a strong emphasis on professional development, employees are encouraged to enhance their skills through continuous learning opportunities while working on cutting-edge cloud technologies. The company's commitment to operational excellence and automation not only drives impactful results but also creates a dynamic work environment where creativity and expertise are valued.

Harrington Starr

Contact Details:

Harrington Starr Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Principal Data Engineer: Platform Reliability & Automation

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Apply Directly through Our Website

When you find a suitable opening like Principal Data Engineer: Platform Reliability & Automation at Harrington Starr, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Principal Data Engineer: Platform Reliability & Automation

Platform Reliability
Automation Practices
CI/CD Frameworks
Python
SQL
Cloud Platforms
Software Engineering Best Practices

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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Craft a Tailored Cover Letter:For a full-time role at Harrington Starr, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Harrington Starr. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Harrington Starr

Brush Up on Your Statistics

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Get Comfortable with Python and R

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Prepare for Case Studies

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