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- Tasks: Design and build innovative data pipelines in the cloud using Python, SQL, and more.
- Company: Curve Analytics is a cutting-edge consultancy transforming consumer data into actionable insights.
- Benefits: Enjoy hybrid working, 25 days holiday, a generous pension, and a personal growth budget.
- Why this job: Join a fast-growing start-up where your work directly impacts clients and shapes the future.
- Qualifications: Bachelor's degree in a relevant field and experience with SQL databases and cloud environments required.
- Other info: Be part of a vibrant culture with team activities and a commitment to diversity and inclusion.
The predicted salary is between 42000 - 84000 £ per year.
This range is provided by Curve Analytics. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
Curve is a next-gen insights, analytics and technology consultancy that leverages digital consumer data and advanced technology to help businesses unlock consumer opportunities. Digital consumer data is powerful; it\’s big, it\’s real, and it\’s always updating. We use a combination of in-house technology and bespoke solutions, powered by AI, to transform data from sources such as Social, Reviews, Search, and broader marketing and sales data. These reveal fresh insights for our clients; helping them to build better products and brands, to deliver effective marketing to consumers.
Our software, machine learning and AI are key to how we deliver impact, centred on:
- Natural Language Processing, GPT & other LLMs: unearthing trends, themes and other patterns from large text-based data sets, and deploying state-of-the-art AI to automate and empower consumer facing businesses and their insights & analytics functions
- Marketing Data Science & Personalisation: using first party consumer data to understand each client\’s consumer base, building personalisation and other machine learning models to better engage with and excite consumers
- Data Engineering & Data Architecture: data engineering across a variety of tools to integrate these leading technologies into optimised and efficient data models and ecosystems, feeding into best-in-class analytics dashboards, marketing activation and front-end platforms
- Software Engineering: full stack expertise to build, maintain and support internal and externally facing Software & Data as a Service solutions, in AWS, that accelerate delivery and unlock deeper insights for our clients
As a start-up, we can move faster than most companies and do things differently. We have experienced rapid growth so far and we’re looking for a Data Engineer to join our growing team.
About the role
You’ll play a crucial role in designing, building and productionising innovative data pipelines, in the cloud, from scratch. You’ll work on a mix of small analytics proof of concepts and larger projects, both of which pushing the boundaries of what we can do with data; finding and using novel data sources and APIs, and enriching them with leading analytics, data science and AI methods.
Your role will be twofold. You’ll be working directly with our London-based client-base, as well as helping to shape the future of our fast-growing start-up. We’ll let you challenge yourself, from your core of data engineering to support our data science and dashboard visualisation work, to grow your cloud architecture and engineering knowledge, and to understand the business and strategic impact of your great engineering work – to whatever extent suits you.
You should be passionate about developing industry first data science and analytics capabilities and have an innovative and creative mindset.
What you’ll be doing
- Build innovative data solutions in Python, PySpark & SQL across Databricks, Snowflake, AWS and more
- Support the development and rollout of industry first global analytics programmes
- Develop and deploy automated code pipelines, from data acquisition, owning transformation and supporting data modelling
- Help to productionise machine learning models and integrate leading APIs from OpenAI, GCP, Microsoft and other open source solutions
- Work closely with great programme teams – project lead, data scientists and analysts – and interface with client technology counterparts
- Identify ways to improve data reliability, processing efficiency and quality of our data output
- Produce detailed documentation and champion code quality
- Interrogate rich data sources such as social, search, surveys, reviews, clickstream, sales, connected devices and beyond
- Identify and explore opportunities to acquire new data sources that deliver innovative perspectives to our clients
What we’re looking for
- Bachelor’s degree or higher in an applicable field such as Computer Science, Statistics, Maths or similar Science or Engineering discipline
- Experience designing, building and maintaining SQL databases (and/or NoSQL)
- Experience with designing efficient physical data models/schemas and developing ETL/ELT scripts
- Strong python and other programming skills (Java and/or Scala desirable)
- Experience developing data solutions in cloud environments such as Azure, AWS or GCP – Azure Databricks & Snowflake experience a bonus
- Strong SQL background
- Some exposure to big data technologies (hadoop, spark, presto, etc.)
Nice to haves or excited to learn
- Experience with APIs
- Experience with Data Science and / or NLP
- Experience of software development, CI/CD pipelines and/or other DevOps practices and principles
- Experience utilising social listening tools and / or search / web analytics tools
- Competitive Salary: We offer a competitive salary, that reflects your talent and expertise in accordance with industry standards. We also conduct quarterly pay reviews throughout the year.
- Annual Leave: 25 days holiday a year plus bank holidays.
- Annual Bonus: Our Annual Bonus is based on company and individual performance.
- Generous Pension: You can expect to receive a generous 8% employers’ pension contribution.
- Health and Wellbeing: Access our Cycle to Work Scheme and prioritise your health with our comprehensive AXA Private Healthcare Plan and 24/7 Employee Assistance Programme. You will also be assigned a dedicated People Manager for confidential discussions about your work life.
- Cycle to Work Schemes: Save on the cost of a brand new bike through the C2W scheme, and have access to monthly minutes with Forest e-bikes.
- Hybrid Working: Split your time between working remotely and from our London HQ.
- Growth and Development: Development is at the heart of everything we do. You will be able to create a Personalised Growth Plan and get involved in our internal trainings. You will also get a yearly individual learning budget for training, books, courses, certifications, and conferences.
- Vibrant Company Culture: Be part of a dynamic company culture with frequent team activities, company events and socials that foster a strong sense of community among our diverse team.
We’re looking for candidates who really want to make an impact. Join us!
Curve is an equal opportunity employer dedicated to building an inclusive and diverse workforce. We do not discriminate on the basis of disability, sex, gender reassignment, sexual orientation, pregnancy and maternity, race, religion or belief and marriage and civil partnerships. All employment is decided on the basis of qualifications, merit, and business need. If you require any reasonable adjustments to be made during the recruitment process then please don’t hesitate to let us know.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Business Consulting and Services
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Data Engineer employer: Curve Analytics
Contact Detail:
Curve Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Python, PySpark, SQL, Databricks, and Snowflake. Having hands-on experience or projects showcasing your skills with these technologies can set you apart from other candidates.
✨Tip Number 2
Network with current employees or alumni who work at Curve Analytics or similar companies. Engaging in conversations about their experiences can provide valuable insights into the company culture and expectations, which you can leverage during interviews.
✨Tip Number 3
Prepare to discuss real-world applications of data engineering in your previous roles. Be ready to share specific examples of how you've built data pipelines or improved data processing efficiency, as this will demonstrate your practical knowledge and problem-solving abilities.
✨Tip Number 4
Stay updated on the latest trends in data engineering and AI technologies. Being able to discuss recent advancements or case studies during your interview can show your passion for the field and your commitment to continuous learning.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with tools like Python, SQL, and cloud environments. Use keywords from the job description to demonstrate your fit for the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and how your skills align with Curve Analytics' mission. Mention specific projects or experiences that showcase your ability to build innovative data solutions.
Showcase Technical Skills: Include a section in your application that lists your technical skills, especially those mentioned in the job description such as ETL processes, machine learning, and experience with APIs. This will help you stand out as a qualified candidate.
Prepare for Technical Questions: Anticipate technical questions related to data engineering during the interview process. Brush up on your knowledge of SQL databases, data modelling, and cloud technologies to confidently discuss your expertise.
How to prepare for a job interview at Curve Analytics
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and cloud environments like AWS or Azure. Bring examples of projects where you've built data pipelines or worked with big data technologies, as this will demonstrate your hands-on expertise.
✨Understand the Company’s Focus
Research Curve Analytics and their approach to leveraging digital consumer data. Familiarise yourself with their use of AI and machine learning in data engineering, as this knowledge will help you align your answers with their business goals during the interview.
✨Prepare for Problem-Solving Questions
Expect to face technical challenges or case studies that require you to think critically about data engineering problems. Practice articulating your thought process clearly, as interviewers will be looking for your ability to tackle complex issues effectively.
✨Demonstrate Your Passion for Innovation
Curve Analytics values creativity and innovation. Be ready to share your ideas on how to improve data solutions or explore new data sources. This will show your enthusiasm for pushing boundaries and contributing to the company's growth.
