Junior Data Engineer

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 Junior Data Engineer to join our growing team.

You will 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 push 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.

• Build innovative data solutions
• Support the development and rollout of an industry-first global analytics programme
• Develop and deploy automated code pipelines, from data acquisition through cleaning and preparing data for modelling, through to visualisation
• Help to productionise machine learning models
• Work closely with a great programme team – 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
• Deploy pipelines in cloud environments and develop as a cloud technologist, as our world becomes increasingly reliant on cloud technologies
• 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

• Bachelor’s degree or higher in an applicable field such as Computer Science, Statistics, Maths or similar Science or Engineering discipline
• Strong Python and other programming skills (Java and/or Scala desirable)
• Strong SQL background
• Some exposure to big data technologies (Hadoop, spark, presto, etc.)

• Some experience designing, building and maintaining SQL databases (and/or NoSQL)
• Some experience with designing efficient physical data models/schemas and developing ETL/ELT scripts
• Some experience developing data solutions in cloud environments such as Azure, AWS or GCP – Azure Databricks experience a bonus

1. 30 minute video interview with the People & Operations Team
2. 45 minute technical video interview with one of our Senior Data Engineers
3. Final interview with our Director of Technology