Hybrid Data Engineer: Shape ETL/ELT & Data Integrations

Hybrid Data Engineer: Shape ETL/ELT & Data Integrations

Full-Time 63000 - 77000 £ / year (est.) Hybrid
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At a Glance

  • Tasks: Design and develop reliable data pipelines and integrations using ETL/ELT processes.
  • Company: Join Black & White Rec, a growing company focused on data innovation.
  • Benefits: Enjoy a competitive salary, flexible working options, and opportunities for growth.
  • Other info: Collaborative hybrid team environment with a focus on continuous improvement.
  • Why this job: Make an impact by ensuring data accuracy and performance for key decision-making.
  • Qualifications: Experience with SQL databases, APIs, and data modelling is essential.

The predicted salary is between 63000 - 77000 £ per year.

Black & White Rec is expanding its data function and seeking a Data Engineer to design, develop, and support reliable data pipelines and integrations.

You will work with ETL/ELT processes, SQL databases, APIs and data models to ensure data accuracy, performance and availability for operational reporting and decision-making.

The role combines project delivery with continuous improvement in a collaborative, hybrid team.

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Hybrid Data Engineer: Shape ETL/ELT & Data Integrations employer: Black & White Rec

Black & White Rec offers a dynamic work environment where professionals can thrive in their respective fields, particularly in Salesforce administration and data engineering. The company emphasizes autonomy and collaboration, allowing employees to contribute meaningfully to projects while ensuring their ideas and technical input are valued. With a focus on professional growth and continuous improvement, Black & White Rec provides opportunities for individuals to shape processes and drive operational success.

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Contact Details:

Black & White Rec Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Hybrid Data Engineer: Shape ETL/ELT & Data Integrations

✨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 Black & White Rec!

✨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 Hybrid Data Engineer: Shape ETL/ELT & Data Integrations at Black & White Rec.

✨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 Black & White Rec.

✨Apply Directly through Our Website

When you find a suitable opening like Hybrid Data Engineer: Shape ETL/ELT & Data Integrations at Black & White Rec, 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 Hybrid Data Engineer: Shape ETL/ELT & Data Integrations

Communication Skills
Python
Data Engineering
Problem-Solving Skills
SQL
Data Warehousing
Data Pipeline Development

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 Black & White Rec, 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 Black & White Rec. 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 Black & White Rec

✨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 Black & White Rec!

✨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.