At a Glance
- Tasks: Design and maintain scalable data pipelines while collaborating with diverse teams.
- Company: Join Huzzle, connecting talent with exciting opportunities globally.
- Benefits: Enjoy competitive pay, remote work, and career growth in a collaborative environment.
- Other info: Work with cutting-edge technologies and gain exposure to emerging data trends.
- Why this job: Tackle complex data challenges and make a real impact on innovative projects.
- Qualifications: 2+ years in data engineering, strong SQL skills, and proficiency in relevant programming languages.
The predicted salary is between 63000 - 77000 £ per year.
At Huzzle, we connect exceptional talent with exciting opportunities at leading companies across the UK, US, Canada, Europe, and Australia. We work with a diverse range of clients, including startups, digital agencies, and technology-driven businesses across industries such as SaaS, MarTech, FinTech, and AI. Unlike traditional outsourcing agencies, we place you directly with our clients, where you become an integral, in-house member of their team.
Job Summary
As a Data Engineer, you will play a key role in designing, developing, and maintaining scalable data pipelines and infrastructure. You will collaborate with data analysts, data scientists, software engineers, and business stakeholders to ensure data is reliable, accessible, and of high quality across the organisation. This is a great opportunity for professionals who enjoy tackling complex data challenges and building robust systems that power business intelligence, analytics, and machine learning initiatives.
Key Responsibilities
- Design, build, and maintain scalable ETL and ELT data pipelines
- Develop and optimize data architectures, databases, and data warehouses
- Integrate data from various sources, APIs, and third-party platforms
- Maintain data quality, accuracy, consistency, reliability, and security
- Monitor, troubleshoot, and improve data pipelines and workflows
- Work closely with analytics, engineering, and business teams to identify and meet data requirements
- Establish data governance standards and best practices for data management
- Improve data storage, processing speeds, and query performance
- Support business intelligence, reporting, and analytics projects
- Maintain documentation of data models, workflows, and technical processes
Requirements
- 2+ years of experience in data engineering, data warehousing, or a similar field
- Strong SQL skills and a solid understanding of database management
- Proficiency in Python, Java, Scala, or other relevant programming languages
- Practical experience with ETL/ELT tools and building data pipelines
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform
- Hands-on experience with modern data warehouse solutions such as Snowflake, Redshift, BigQuery, or Databricks
- Knowledge of workflow orchestration tools such as Airflow or Prefect
- Understanding of data modelling, governance, and data quality best practices
- Experience handling large datasets and working with distributed systems is an advantage
- Strong analytical thinking, problem-solving, and communication abilities
- Comfortable working independently while collaborating with a remote team
Benefits
- Competitive compensation: Tailored to your experience, technical skills, and location.
- Fully remote work: Enjoy the flexibility to work from anywhere.
- Career development: Join innovative companies and contribute to meaningful, high-impact projects.
- Long-term potential: Grow your career alongside ambitious, expanding global organisations.
- Ongoing learning: Gain exposure to emerging data technologies, cloud platforms, and large-scale data environments.
- Collaborative environment: Work with skilled engineers, analysts, and business stakeholders.
- Modern tech stack: Work with cutting-edge data tools, technologies, and cloud-based solutions.
Data Engineer employer: Huzzle.com
Huzzle Labs is an exceptional employer, offering a dynamic work environment that fosters innovation and collaboration across its global locations, including Palo Alto, London, and Berlin. With a strong emphasis on employee growth, you will have the opportunity to lead impactful projects in frontier AI, while being supported by a culture that values clear communication and ownership. Join us to be part of a cutting-edge team where your contributions directly influence the future of AI technology.
StudySmarter Expert Advice🤫
We think this is how you could land Data 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 Huzzle.com!
✨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 at Huzzle.com.
✨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 Huzzle.com.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer at Huzzle.com, 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
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 Huzzle.com, 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 Huzzle.com. 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 Huzzle.com
✨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 Huzzle.com!
✨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.
