The CompanyA leading AI consulting firm specializing in leveraging data to drive business value. Known for delivering cutting-edge solutions in Natural Language Processing, GenAI, LLMs, Predictive Analytics, and Machine Learning, they help clients optimize operations, enhance customer experiences, and gain a competitive edge.
The RoleBuilding modern database structures storing terabytes of data used to develop and maintain machine learning models in a cloud environment.Collaborate with Software Engineering stakeholders and Leads to define and implement new data-powered solutions and deploy and maintain them in production.Supporting best practices in cataloguing, characterising, classifying and communicating accessible data and initiatives relative to data creation so teams can easily access the data.Creating and owning best practices in terms of data 'organisation', standards and versioning including in a Cloud environment.Own data privacy and security standards according to GDPR and apply these to production systems.Embracing modern DevOps principles and working in a setting where code is expected to be shared and peer-reviewed.Experience3 years experience with data wrangling/data engineering, implementing, and supporting robust data transformation pipelines in a production Cloud environment.RDBMS systems for OLTP workloads, such as Postgres or MySQL.Implementing methods to ensure large-scale (big data) quality and security.Software design patterns and test-driven development.Experience working with big data technologies such as Spark, Hadoop, Presto, Hive, AWS Athena and Terraform.Dynamic languages, such as Python or R.Container technology, like Docker.Experience with JavaScript frameworks like Vue, Node.js.
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