At a Glance
- Tasks: Develop and optimise data pipelines while collaborating with diverse teams.
- Company: Join a forward-thinking organisation that values innovation and teamwork.
- Benefits: Competitive salary, flexible working options, and opportunities for skill development.
- Other info: Be part of a vibrant community focused on continuous improvement and growth.
- Why this job: Make a real impact by enhancing data processes and driving business decisions.
- Qualifications: Experience in data engineering or related fields, with strong analytical skills.
The predicted salary is between 55000 - 65000 £ per year.
Curious about an exciting opportunity to develop your career as a Data Engineer?
We’re looking for someone with technical skills but also a great attitude, who is proactive, takes pride in the quality of their work and is eager to continually improve their technical skills.
We welcome applications from varied technical backgrounds including but not limited to: data science, infrastructure engineering, software engineering or related technical disciplines.
Responsibilities
- Work across the lifecycle of ETL/ELT (extract, transform, load / extract, load, transform) pipelines that facilitate the movement and transformation of data across our systems.
- Conduct data profiling and analysis to assess data quality, identify anomalies, and uncover insights that inform data pipeline design and business decision-making.
- Develop and maintain internal software packages for Data Engineering.
Use tools across ourtech-stacks, such as SQL, Python, Py Spark, Cloudera Data Platform, Google Cloud Platform.
- Optimise the performance of our queries and data pipelines.
Collaborate with various technical and business stakeholders to develop and deliver on requirements, to ensure our data and processes meet business needs.
- Set, follow and ensure adherence to standard ways of working and good practice in Data Engineering.
Ensure governance and compliance of our data and processes in line with ONS policies and wider legal requirements.
- Contribute to the evaluation and adoption of new tools, frameworks, and technologies that enhance the data engineering ecosystem.
- Champion the role of Data Engineers within ONS and participate in ONS and Civil Service Data Engineering communities.
- Take an active role in building the capability of Data Engineers within ONS
- #J-18808-Ljbffr
Senior Data Engineer in Newport employer: Office for National Statistics
As a Quality Specialist with us, you'll thrive in a supportive and flexible work environment that prioritises your well-being and professional growth. Our hybrid working model allows you to balance office and remote work, while our generous benefits, including a market-leading pension scheme and extensive learning opportunities, ensure you feel valued and empowered. Join a diverse team committed to innovation and collaboration, making a meaningful impact on government data and statistics.
Contact Details:
Office for National Statistics Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer in Newport
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We think you need these skills to ace Senior Data Engineer in Newport
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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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Office for National Statistics. 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 Office for National Statistics
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Office for National Statistics!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
