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- Tasks: Design and develop scalable data pipelines using Python for the Net-Zero Data Public Utility.
- Company: Join a forward-thinking team dedicated to providing open and accessible public good data.
- Benefits: Enjoy flexible working options, mentorship opportunities, and a collaborative environment.
- Why this job: Make a real impact on data accessibility while working with cutting-edge technology and talented professionals.
- Qualifications: 7+ years in data engineering, strong Python skills, and experience with data pipelines required.
- Other info: Opportunity to mentor junior team members and shape the future of data engineering.
The predicted salary is between 48000 - 72000 £ per year.
Senior Data Engineer
Location
London
Business Area
Engineering and CTO
Ref #
10043243
Description & Requirements
The NZDPU Tech Team is actively searching for an experienced Senior Data Engineer to play a pivotal role in the design, implementation, enhancement, and maintenance of scalable data pipelines for the Net-Zero Data Public Utility. These pipelines are essential for the Utility's mission of providing open and accessible public good data through both the NZDPU website and APIs.
A successful candidate will face the challenge of working with data originating from a wide array of sources, each with its own formats, fields, and access protocols. Your responsibilities will encompass the full data lifecycle from the extraction of data from sources, transforming it according to source and domain specific business logic, and pushing it through the Utility's ingestion process. Additionally, you will be expected to implement data quality checks and validation procedures to ensure the accuracy and reliability of the data provided by the Utility.
Responsibilities:
- Design and develop scalable data pipelines using Python to read from APIs and structured files (Excel, Parquet).
- Translate domain and source specific business logic into efficient code implementations to turn source data into usable structured data for downstream applications.
- Implement data transformations and structuring using tools like Pandas and Pydantic to ensure data quality, consistency, and adherence to business logic requirements.
- Collaborate with data scientists and analysts to support data-driven decision-making.
- Document data engineering processes, including data lineage, data dictionaries, and system architectures
- Maintain best practices through code reviews, version control, and adherence to industry standards.
- Deploy production quality code through CI/CD pipelines into our cloud environment.
- Provide mentorship and guidance to junior team members, fostering their growth and development in data engineering practices.
Qualifications
- 7+ years of experience in data engineering or a similar role.
- Proficiency in Python programming.
- Experience with building and managing data pipelines.
- Knowledge of data warehousing and ETL processes.
- Excellent problem-solving and communication skills.
Senior Data Engineer employer: Bloomberg
Contact Detail:
Bloomberg Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Python, Pandas, and Pydantic. Having hands-on experience or projects that showcase your skills with these tools will make you stand out during the interview process.
✨Tip Number 2
Prepare to discuss your experience with data pipelines and ETL processes in detail. Be ready to share specific examples of challenges you've faced and how you overcame them, as this will demonstrate your problem-solving abilities and practical knowledge.
✨Tip Number 3
Network with current or former employees of StudySmarter or similar companies. Engaging with them on platforms like LinkedIn can provide valuable insights into the company culture and expectations, which can help you tailor your approach during interviews.
✨Tip Number 4
Showcase your mentorship experience if applicable. Since the role involves guiding junior team members, highlighting any previous mentoring or leadership roles can demonstrate your ability to contribute positively to the team dynamic.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering, particularly with Python and building data pipelines. Use specific examples that demonstrate your skills in handling various data formats and implementing data quality checks.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the mission of the Net-Zero Data Public Utility. Discuss how your background aligns with the responsibilities outlined in the job description, especially your experience with data transformations and collaboration with data scientists.
Showcase Relevant Projects: If you have worked on projects that involved designing scalable data pipelines or using tools like Pandas and Pydantic, be sure to mention these. Highlight any specific challenges you faced and how you overcame them, as this will demonstrate your problem-solving skills.
Proofread Your Application: Before submitting your application, carefully proofread all documents for spelling and grammatical errors. A polished application reflects attention to detail, which is crucial in data engineering roles.
How to prepare for a job interview at Bloomberg
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and data pipeline development. Bring examples of past projects where you've designed and implemented scalable data solutions, and be ready to explain the challenges you faced and how you overcame them.
✨Understand the Business Context
Familiarise yourself with the mission of the Net-Zero Data Public Utility. Understanding how your role as a Senior Data Engineer contributes to providing open and accessible public good data will demonstrate your alignment with the company's goals.
✨Prepare for Problem-Solving Questions
Expect to encounter technical problem-solving scenarios during the interview. Practice explaining your thought process clearly and logically, as this will showcase your analytical skills and ability to tackle complex data challenges.
✨Emphasise Collaboration and Mentorship
Highlight your experience working with data scientists and analysts, as well as any mentorship roles you've taken on. This will show that you value teamwork and are committed to fostering growth within the team, which is crucial for a senior position.
