Python, SQL, ETL, AWS, PySpark, APIs, CI/CD, Snowflake
Logistics
Hybrid
Curve is a next-gen insights and analytics consultancy that leverages digital consumer data and advanced technology to help businesses unlock consumer opportunities.
Digital consumer data is powerful; We transform data from sources such as Social, Reviews, Search, and Web to reveal fresh insights for our clients; helping them to build better products and brands, and 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
Analytics 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 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
We have experienced rapid growth so far and we're looking for a 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.
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
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
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
30 minute video interview with the People & Operations Team
~60 minute technical video interview with one of our Senior Data Engineers
~ Final video interview with our Director of Technology
Curve is an equal opportunity employer dedicated to building an inclusive and diverse workforce.
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