At a Glance
- Tasks: Develop and optimise ETL processes using Databricks and create robust data pipelines.
- Company: Join Peabody, a leading non-profit organisation focused on community impact.
- Benefits: Enjoy flexible benefits, additional paid volunteering days, and a strong pension contribution.
- Other info: Collaborative environment with opportunities for innovation and career growth.
- Why this job: Make a meaningful impact by delivering cutting-edge Azure data solutions.
- Qualifications: Proficient in SQL, experienced with Databricks, and knowledgeable in data governance.
The predicted salary is between 36000 - 60000 £ per year.
Join to apply for the Azure Data Engineer role at Peabody. Specialising in recruitment of corporate roles for Peabody Housing Group.
Job details:
- Number of Positions: 1
- Contract Type: Permanent, Full Time
- Working Hours: 35
Our Vacancy:
As an Azure Data Engineer, you’ll be responsible for developing and optimising ETL processes using Databricks, crafting robust data pipelines, and ensuring seamless integration into Data Lakes and other storage solutions. You’ll apply best practices in data management, governance, and quality assurance, while building secure and accessible data architectures that support a cohesive data ecosystem. You’re a people person who likes to get things done. You’ll enjoy working collaboratively with data scientists, analysts, and stakeholders to understand business needs and deliver tailored solutions. You’ll also partner with IT, Digital, and DevOps teams to ensure smooth deployment and integration of data services, while offering technical guidance and mentorship to fellow engineers. You’ll need to be in the office for a minimum of 2 days per week. We’re looking for someone who thrives on innovation and continuous improvement. You’ll stay ahead of the curve with the latest trends in big data technologies, evaluate existing processes, and identify opportunities for automation and optimisation. Your contributions will help define and elevate data engineering standards across the organisation. If you’re passionate about data and ready to make a meaningful impact, we want to hear from you.
Success in this role means:
- Delivering cutting-edge Azure data solutions, transforming key data sources to enhance reporting and analytics, and building trustworthy, well-documented data pipelines that improve property services and resident experience.
To be successful in this role, you’re:
- Proficient in advanced SQL and experienced in migrating SSIS packages to Databricks.
- Certified in cloud platforms, ideally holding the Azure Data Engineer Associate certification.
- Deeply knowledgeable in ETL/ELT processes, data warehousing, and data modelling.
- Equipped with strong technical expertise in Databricks, including hands-on experience with Spark, Delta Lake, and MLflow.
- Experienced in implementing enterprise-grade data governance and security standards.
- Capable of resolving complex data issues with precision, insight, and a solutions-oriented mindset.
Here are just a few of the benefits of working at Peabody:
- Two additional paid volunteering days each year.
- Flexible benefits scheme, including family friendly benefits and access to a discount portal.
- 4 x salary life assurance.
- Up to 10% pension contribution.
Interviews will be taking place on 8th September 2025. Are you ready to apply? If you have any questions about this role, please email Talent Specialist, Harry at harry.lund@peabody.org.uk. We may close this advert before the advertised closing date, depending on the number of applications received.
PLEASE NOTE: As an employer, Peabody does not provide sponsorship as a licenced UK employer.
Seniority level: Associate
Employment type: Full-time
Job function: Information Technology
Industries: Non-profit Organizations
Azure Data Engineer in London employer: Peabody
Peabody is an exceptional employer that prioritises innovation and collaboration, offering a dynamic work culture where your contributions directly impact the lives of residents. With a strong commitment to employee growth, you will have access to professional development opportunities and the chance to lead transformative projects in a hybrid work environment, making a meaningful difference in the community.
StudySmarter Expert Advice🤫
We think this is how you could land Azure Data Engineer in London
✨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 Peabody!
✨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 Azure Data Engineer at Peabody.
✨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 Peabody.
✨Apply Directly through Our Website
When you find a suitable opening like Azure Data Engineer at Peabody, 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 Azure Data Engineer in London
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 Peabody, 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 Peabody. 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 Peabody
✨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 Peabody!
✨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.
