At a Glance
- Tasks: Design and build scalable data pipelines for a leading global organisation.
- Company: Join a top-tier global organisation with a focus on innovation.
- Benefits: Competitive pay up to £900 per day, hybrid work model, and career growth.
- Other info: Collaborate with engineers and data scientists in a high-performing team.
- Why this job: Make an impact by developing cutting-edge data solutions in a dynamic environment.
- Qualifications: Strong Python skills and experience with data engineering and cloud platforms.
The predicted salary is between 72000 - 90000 £ per year.
Client: Leading Global Organisation
Salary: Up To £900 Per Day
Location: London (Hybrid)
Skills: Python, Data Pipelines, Dagster, Airflow, Snowflake, AWS, S3, IAM, APIs, Streaming & Batch Data
The Role
We’re working with a leading global organisation to hire an experienced Data Engineer to help build and scale modern data platforms that power analytics, trading, and operational decision-making. This is a hands-on engineering role within a high-performing data and business engineering environment. You’ll work closely with engineers, data scientists, and business stakeholders to design and deliver robust data solutions, develop production-grade pipelines, and support the ongoing evolution of the organisation’s data platform.
Responsibilities
- Design, build, and maintain scalable data pipelines and data platform components
- Develop Python-based data workflows using orchestration tools such as Dagster or Airflow
- Extract and integrate data from internal systems, external sources, and APIs
- Support the development and optimisation of cloud-based data platforms, including Snowflake
- Integrate batch and streaming data flows where required
Requirements
- Strong hands-on experience in data engineering
- Solid programming skills in Python (Java is a plus)
- Experience building and operating production data pipelines
- Experience working with modern cloud data platforms or warehouses (e.g., Snowflake)
- Familiarity with AWS data infrastructure such as S3 and IAM
If you're a hands-on Data Engineer who enjoys building scalable data platforms and delivering high-quality data solutions, we’d love to hear from you.
Senior Data Engineer: Build Scalable Pipelines (Hybrid) employer: Hunter Bond
Join a leading global organisation that values innovation and collaboration, offering a dynamic work culture where your contributions directly impact analytics and operational decision-making. With competitive pay of up to £900 per day and a hybrid working model in London, you'll have the flexibility to thrive while developing your skills alongside top-tier engineers and data scientists. This role not only provides hands-on experience with cutting-edge technologies but also fosters continuous professional growth in a supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer: Build Scalable Pipelines (Hybrid)
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the lookout for opportunities. You never know who might have a lead or can refer you to a hiring manager.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, data pipelines, and cloud platforms like Snowflake. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with tools like Dagster, Airflow, and AWS. Practising common data engineering interview questions can really help you stand out.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge over other candidates. Let’s get you that dream job!
We think you need these skills to ace Senior Data Engineer: Build Scalable Pipelines (Hybrid)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, data pipelines, and cloud platforms like Snowflake. We want to see how your skills match the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you’re passionate about data engineering and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love a good story!
Showcase Your Projects:If you've worked on any cool data projects, make sure to mention them! Whether it's building scalable pipelines or using tools like Dagster or Airflow, we want to know what you've done and how it relates to the role.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Hunter Bond
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, Snowflake, and orchestration tools like Dagster or Airflow. Brush up on your knowledge of AWS services like S3 and IAM, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built scalable data pipelines or worked with cloud data platforms. Be ready to explain your role, the challenges you faced, and how you overcame them. This will demonstrate your hands-on experience and problem-solving skills.
✨Understand the Business Impact
Research the company and understand how their data solutions impact their analytics and trading operations. Being able to articulate how your work as a Data Engineer can contribute to their business goals will set you apart from other candidates.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, the data challenges they face, and the future of their data platform. This shows your genuine interest in the role and helps you assess if the company is the right fit for you.
