Want to work on the latest cloud SQL and graph technology at the centre of our Saas Platform?

Cube is the leading provider of regulatory intelligence to sophisticated, globally-regulated organisations.  We do this by sourcing, enriching and serving regulatory data and functionality via our platform.

As Senior Data Engineer you will be instrumental in designing, automating and managing how data is stored, shared and analysed throughout our platform.  You will be key player in implementing new technologies to handle the richness of our regulatory and user interaction data.   

The kind of things you will be doing:

• Working with data scientists in our RegBrain team to understand and deliver data flows into and out of machine learning operations
• Working with Application Engineering to design and implement storage and access strategies for user interaction data
• Helping to build our data analytics capability, working across all our Data Science, Engineering and Data Management teams

What it's like to work at Cube

Cube is a fast-paced,  innovative firm where new ideas and technologies are encouraged, since we are always looking for ways to improve how and what we deliver.  

We embrace a work-from-home culture: it breeds productivity, is more efficient, and enables our employees to be more flexible and engaged, with transformative online solutions and infrastructures in place. On top of that we significantly reduce our carbon footprint.

The kind of tech you will be familiar with:

• SQL.  Ability to understand and compose complex queries, design schema, tune performance.
• Cloud data. Experience with one or more major cloud vendors and their database technology.   
• Data transport.  Experience moving data across environments, into different database types.
• NoSql.  Experience with index, document store, graph dbs.
• Caching. Services that sit in front of data stores to increase performance
• Message Buses.  Services to manage eventual consistency or event sourcing.
• Analytics.  Tech that enables self-service analytics, e.g. PowerBI, Tableau.
• Data cleansing. Using tools and writing code to detect data quality issues, clean data, strip html etc