Lead Data Engineer β€” Azure Data & AI Pipelines in Warwick

Lead Data Engineer β€” Azure Data & AI Pipelines in Warwick

Warwick Full-Time 63000 - 77000 Β£ / year (est.) Hybrid
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At a Glance

  • Tasks: Create data pipelines and dashboards using Azure and Snowflake to drive insights.
  • Company: Join National Grid, a leader in energy innovation and sustainability.
  • Benefits: Enjoy hybrid work, competitive pay, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on data quality and governance.
  • Why this job: Make a real difference by transforming business challenges into data solutions.
  • Qualifications: Experience in data engineering and a passion for cloud technologies.

The predicted salary is between 63000 - 77000 Β£ per year.

National Grid is seeking an Associate Data Developer in Warwick.

The role operates in a hybrid model and focuses on delivering actionable insight across the data lifecycle, from ETL development to dashboards, using cloud platforms such as Azure and Snowflake.

The successful candidate will collaborate with stakeholders to translate business challenges into data-driven solutions, implement CI/CD pipelines, and ensure data quality and governance across pipelines and AI-enabled workflows.

Lead Data Engineer β€” Azure Data & AI Pipelines in Warwick employer: National Grid

At National Grid, we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters innovation and collaboration. With competitive salaries, generous bonuses, and a robust pension scheme, we ensure our employees are well rewarded for their contributions. Our commitment to diversity and inclusion, along with flexible working arrangements, empowers our team members to thrive both personally and professionally in the heart of the UK's energy sector.

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Contact Details:

National Grid Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Lead Data Engineer β€” Azure Data & AI Pipelines in Warwick

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like National Grid!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead Data Engineer β€” Azure Data & AI Pipelines at National Grid.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like National Grid.

✨Apply Directly through Our Website

When you find a suitable opening like Lead Data Engineer β€” Azure Data & AI Pipelines at National Grid, 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 Lead Data Engineer β€” Azure Data & AI Pipelines in Warwick

Python
Communication Skills
Data Engineering
SQL
Problem-Solving Skills
ETL/ELT Processes
Data Warehousing

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!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at National Grid, 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 National Grid. 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 National Grid

✨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!

✨Showcase Your Projects

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 National Grid!

✨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.