At a Glance
- Tasks: Ensure data health and maintain effective data pipelines for analytics tools.
- Company: Hexegic, a leading technical consultancy with exciting projects.
- Benefits: Competitive salary, professional development budget, wellness program, and hybrid working.
- Other info: Enjoy 25 days annual leave and excellent career growth opportunities.
- Why this job: Join a dynamic team and make a real impact on data-driven projects.
- Qualifications: Proficient in Python and PySpark, with a basic understanding of Spark.
You will ensure our customer works with updated and correct data in our data analytics tools by being the first to respond to data health failures on key pipelines, reading code and making changes.
About us: Hexegic are a leading technical consultancy providing agile multi-disciplinary teams to high performing organisations. The company promises exciting, engaging and rewarding projects for those that are keen to develop and build a successful career.
Core Responsibilities:
- Maintain build schedules so that pipelines run effectively
- Set up and maintain health checks on data pipelines
- Respond, triage and debug the pipelines when broken
- Read and make changes to code, and modify monitoring set-ups
- Communicating outages to end users
What we are looking for:
- Comfortable reading and writing code in Python, PySpark
- Basic understanding of Spark
- Ability to navigate pipeline development tools
What’s in it for you?
- Base salary of £50,000-£60,000
- £5000 a year professional development budget
- Wellness program
- 25 days annual leave
- Hybrid working arrangements
Please note that successful candidates must be eligible for UK security clearance.
Data Pipeline Engineer employer: Hexegic
Hexegic is an exceptional employer that prioritises the professional growth and well-being of its employees, offering a generous £5,000 annual development budget and a comprehensive wellness programme including private healthcare. With a collaborative work culture in London, employees are encouraged to contribute to innovative projects in a secure environment, ensuring both personal and professional fulfilment while working alongside a talented team dedicated to making a meaningful impact.
StudySmarter Expert Advice🤫
We think this is how you could land Data Pipeline 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 Hexegic!
✨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 Pipeline Engineer at Hexegic.
✨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 Hexegic.
✨Apply Directly through Our Website
When you find a suitable opening like Data Pipeline Engineer at Hexegic, 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!
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 Hexegic, 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 Hexegic. 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 Hexegic
✨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 Hexegic!
✨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.
