At a Glance
- Tasks: Design and build scalable data pipelines using Databricks, AWS, and Python.
- Company: Join a tech-led organisation transforming data into strategic insights.
- Benefits: Training opportunities, hybrid working, and a supportive team culture.
- Other info: Collaborative environment with opportunities for mentorship and career development.
- Why this job: Make a real impact on business growth through innovative data solutions.
- Qualifications: Experience with Databricks, Python, SQL, and cloud platforms like AWS.
The predicted salary is between 60000 - 80000 £ per year.
We're partnering with a growing technology-led organisation that delivers critical services across highly regulated sectors. They're investing heavily in their data platform and are looking for an experienced Data Engineer to help shape the future of their data architecture.
You’ll play a key role in building scalable data pipelines, driving engineering best practice, and enabling advanced analytics across the business. This is an opportunity to join a company where data is becoming increasingly central to strategic decision-making.
What you’ll do
You’ll be joining a collaborative data team where you’ll help design, build and optimise modern data solutions using Databricks, AWS and Python. This is an opportunity to influence architectural decisions, mentor colleagues and work on impactful projects that directly support business growth and transformation.
Requirements
- Strong commercial experience with Databricks, Spark and Delta Lake
- Proven experience designing and building scalable ETL/ELT pipelines
- Strong Python and SQL skills
- Experience working with cloud platforms (AWS preferred)
- Knowledge of data modelling, data architecture and governance
- Experience with orchestration tools such as Airflow or Databricks Workflows
- Comfortable working closely with stakeholders, working independently delivering on high‑profile projects and mentoring team members
- Experience delivering complex data solutions from scratch
Hybrid Working Pattern
This will be 3 days a week onsite and 2 days a week offsite – you will be liaising & working collaboratively with the consultancy partners as well as the data analytics team.
Benefits
- Opportunity to influence a growing data function
- Training and development opportunities
- Collaborative and supportive culture
Data Engineer (Databricks, AWS) in Stretford employer: FORT
Join a forward-thinking technology-led organisation that prioritises data as a cornerstone of strategic decision-making. With a collaborative culture and a strong focus on employee development, you'll have the chance to influence architectural decisions and work on impactful projects while enjoying a hybrid working model that promotes work-life balance. This is an excellent opportunity for growth in a dynamic environment where your contributions will directly support business transformation.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (Databricks, AWS) in Stretford
✨Get Involved in Data Science Meetups
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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 FORT.
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We think you need these skills to ace Data Engineer (Databricks, AWS) in Stretford
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 FORT, 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 FORT. 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 FORT
✨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 FORT!
✨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.
