At a Glance
- Tasks: Design and maintain scalable data pipelines, automate processes, and build performance dashboards.
- Company: Join a mission-driven company focused on making a positive impact in the world.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and continuous improvement.
- Why this job: Be part of a team that champions data quality and drives real change.
- Qualifications: Strong SQL and Python skills, experience with Databricks and data modelling.
The predicted salary is between 63000 - 77000 £ per year.
Help us make a big green dent in the universe.
Key Responsibilities
- Design, build, and maintain scalable data pipelines in Databricks, ensuring data is reliable, timely, and well-documented.
- Own and evolve our Databricks models - define schemas, enforce testing, and keep the warehouse clean.
- Automate manual data processes using Python, replacing spreadsheets and ad-hoc workflows with robust, repeatable jobs.
- Build performance dashboards and reports in Streamlit and HTMX (Fast API) that Finance, Asset Management, and Fund Management actually use.
- Integrate internal and third-party systems via REST APIs, improving data accessibility across the business.
- Champion data quality - implement validation, monitoring, and governance practices that give stakeholders confidence in the numbers.
- Collaborate directly with non-technical teams to understand their problems and translate them into data solutions.
Requirements
- Strong SQL and Python skills, used daily for pipeline development, data modelling, and automation.
- Experience with modern data stack tooling: a cloud data platform (Databricks preferred), and version control (Git/Git Hub).
- A solid understanding of data modelling, warehousing patterns, and ETL/ELT design.
- To be comfortable working with Postgres or similar relational databases.
- Clear communication - you can explain a data model to a fund manager and discuss trade-offs with an engineer.
- A bias toward shipping: you’d rather get something working and iterate than spend weeks in design.
- #J-18808-Ljbffr
Data Engineer employer: NextGenEnergyJobs
As an Enterprise Architect Director at our company, you will thrive in a dynamic and innovative environment that champions professional growth and collaboration. We offer competitive benefits, a culture that values diversity and inclusion, and opportunities to lead transformative projects that shape the future of Enterprise AI. Join us in a location that fosters creativity and connection, where your leadership will directly impact our success and the satisfaction of our clients.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨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 NextGenEnergyJobs!
✨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 Data Engineer at NextGenEnergyJobs.
✨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 NextGenEnergyJobs.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer at NextGenEnergyJobs, 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 Data Engineer
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 NextGenEnergyJobs, 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 NextGenEnergyJobs. 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 NextGenEnergyJobs
✨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 NextGenEnergyJobs!
✨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.
