At a Glance
- Tasks: Build and maintain data pipelines, automate processes, and ensure data quality.
- Company: Dynamic fintech consultancy with a focus on innovation and collaboration.
- Benefits: Competitive salary up to £120k, bonus, healthcare, generous holiday, and pension.
- Other info: Enjoy a vibrant office atmosphere with social events and flexible working hours.
- Why this job: Join a fast-paced environment and shape your career in data engineering.
- Qualifications: Strong academic background and experience with Databricks, SQL, and Python.
The predicted salary is between 108000 - 120000 £ per year.
Data Engineer (Python Databricks SQL) Take the next step in your career now, scroll down to read the full role description and make your application. *Newcastle Onsite * to 120k Do you have a first class education combined with Data Engineering skills?You could be progressing your career at a scaling Technology Consultancy within the finance division.
What's in it for you: As a Data Engineer you will earn a competitive package: Salary to 120k Bonus25 days holiday Bupa healthcare Generous pension contribution Continuous career development opportunities Social team atmosphere with a range of events and early finish for drinks on Fridays Your role: As a Data Engineer you will work closely with front office teams to understand and define their data needs, ensuring that data capabilities align with business objectives.
You'll contribute to the ongoing development and operation of the firm's data platform, leveraging both in-house and third-party data tools to deliver scalable and efficient solutions.
A key focus will be on analysing and automating data-related processes, identifying opportunities to streamline workflows and reduce manual intervention.
You will be responsible for building and maintaining data pipelines from a variety of external providers, ensuring the seamless integration of high-quality data into the firm's core platform.
Additionally, you'll curate and manage both internal and external datasets to support the front office's analytical and operational requirements.
This will include designing and implementing pragmatic, best-practice data models and architectures that are fit for purpose in a fast-paced environment.
You'll also play a key role in establishing and enforcing data standards and quality controls, helping to ensure the integrity, consistency, and reliability of data across the organisation.
Location / WFH: You'll join colleagues in brand new Central Newcastle offices on a full-time basis (Monday to Friday), working hours with some flexibility.
The offices are well equipped and offer fantastic views across the City and the local countryside, many employees walk or cycle in (onsite showers available! xrnqpay ).
About you: You have an academic record of achievement, minimum 2.1 at BSc from a top tier university, Computer Science or similar technical / scientific discipline, backed by minimum A A B grades at A-level You have commercial Data Engineering experience and a strong understanding of modern data engineering best practices You have experience with Databricks, ideally also Azure You have experience of working with technologies such as SQL, Apache Spark and Python including Py Spark and Pandas You're excited to join a start-up in a role that you can shape and influence You're collaborative with excellent communication skills Apply now to find out more about this Data Engineer (Python Databricks SQL) opportunity.#LI-DNI
Data Engineer SQL Databricks - Fintech employer: Client Server
Join a dynamic and innovative FinTech company that values technical expertise and offers a collaborative work culture. With a competitive salary of up to £100k plus bonuses, you'll have the opportunity to make a significant impact while enjoying hybrid working arrangements in London. The company prioritises employee growth, providing ample opportunities for career progression and staying at the forefront of emerging technologies in the finance sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer SQL Databricks - Fintech
✨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 Client Server!
✨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 SQL Databricks - Fintech at Client Server.
✨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 Client Server.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer SQL Databricks - Fintech at Client Server, 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 SQL Databricks - Fintech
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 Client Server, 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 Client Server. 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 Client Server
✨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 Client Server!
✨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.
