Their people are truly at the heart of everything this company does. From their colleagues delivering ground-breaking solutions to the customers who use them: people have helped them grow for more than thirty years, and people are driving their future as a great SaaS company. They’re writing their next chapter. Be part of it!

Our client recognize that the world of work has rapidly shifted over the last few years, particularly how we work. That is why they have committed to working in a hybrid way going forward. Human connection is an essential ingredient of the 4 principles that make up their Flexible Human Work hybrid framework and they want to be transparent in what that looks like when you join their family. On one hand, their offices will continue to play an important role in their future and serve as a place for spontaneous conversations, connection, collaboration as well as focused time. On the other hand, they have learned to reimagine where and when they work and to unlock that flexibility and innovation for their colleagues offering them the opportunity to work flex across their home, company offices or customer sites.

Truly a company that focuses on their Diversity & Inclusion policy and wants to improve their female employee to male employee ratio #womenintech

The role…

• Work closely with our Data Scientists and ML engineers to build data warehouses and pipelines
• Collaborate with our AI Infrastructure team to extend the capabilities of our machine learning platform
• Monitor and optimize the quality and performance of our data pipelines and tools
• Collaborate with other teams to integrate new data sources, ensuring privacy and security protocols are followed
• Collaborate with data scientists and ML engineers to design and build data analytics tools for detecting data anomalies and ensuring data quality
• Design, implement, and operate pipelines that deliver data with measurable quality and SLOs
• Creating tools for establishing common data management patterns across our team and beyond
• Write production-quality code to support our data pipelines and machine learning systems
• Inform our strategy for data governance, security, privacy, quality, and retention
• Work with our AI Infrastructure team to extend our capabilities , curate new data sets, and manage the data that drives our machine learning platform
• Work with ML Engineers and Data Scientists to refine and specify data products that satisfy business policies and requirements
• Exploratory data analyses and investigations.

You will have…

• 2+ years of relevant practical experience working on data integration, data modelling and metadata management
• Expert knowledge and experience with several relevant languages, tools and frameworks: e.g. Python, SQL, Scala, Spark
• Database experience: e.g. you know how to write and optimize SQL queries, design efficient schemas for OLAP and OLTP and understand differences and tradeoffs between them
• Willingness to adapt to significant changes in either technology or environment
• Bachelor’s degree, preferably in a field that requires data management and manipulation (e.g. statistics, applied math, computer science, or a science field with direct statistics applications)
• Fluency in data fundamentals: SQL, data management, and data manipulation using a procedural language,
• Strong quantitative and analytical skills with minimum 2 years of experience with building data-intensive applications,
• experience with one or more workflow management technology: airflow, argo, etc.
• Deep understanding of relational as well as big data techniques and technologies (e.g. Postgres/mysql, spark, data warehousing (s3, Redshift, Snowflake, etc.))
• Ability to communicate complex ideas to non-technical stakeholders and alternate between big-picture and implementation.

Benefits…

• 15% bonus (50% personal performance, 50% business performance)
• 25 days holiday + 8 bank holidays + 5 learning days + 5 charity days
• Up to 18% total pension with top ups
• 50% income protection for 2+ years
• Flexible working, hybrid or fully remote
• Paternity and maternity leave
• Medical insurance salary sacrifice, cycle to work, mental health memberships, gym classes + more