Renaissance® is a global leader in education technology. We help schools and school groups in the UK and around the world with educational assessments, practice and intervention solutions, and data analytics. Renaissance now incorporates GL Assessment (known internationally as GL Education), too – a leading provider of educational assessments.
Together, our assessments offer the ideal starting point to help teachers understand their students’ strengths and pinpoint areas of need. Our teaching and learning tools then provide effective next steps, with online literacy and maths solutions that meet students exactly where we are.
Worldwide, we support over 18 million students, operating in over 100 countries.

SKILLS AND EXPERIENCE REQUIRED:

To be considered for the role of Data Engineer , we are looking for someone with experience with cloud-based data platforms such as Azure or AWS.

You will also have:

• Strong communication and collaboration skills.
• Experience working with complex data.
• A logical approach to problem solving.
• Strong understanding of data modelling, data pipelines and ETL processes.
• Knowledge of data structures and experience querying and tuning databases.

As our Data Engineer, we are looking for someone who aligns with Renaissance’s mission to accelerate learning for all children and adults of all ability levels and ethnic and social backgrounds, worldwide, we are looking for someone who is/ has:

• Ability to communicate clearly at all levels and across functions
• Proficiency in SQL and other programming languages commonly used in data analytics (e.g., Python, R).
• Experience with Microsoft Azure data services.
• Experience working within a DevOps culture
• Strong engagement with senior colleagues, individually and as a team
• Champions positive change
• Effective management of time and priorities and impacts
• Motivated to make a positive difference in the lives of teachers and children worldwide

ABOUT THIS ROLE:

Renaissance Global are recruiting for a Mid-Level Data Engineer to join our growing team.
Working as part of the Data Engineering team you will be responsible for the design and management of our data and data systems ensuring alignment with strategy and surfacing meaningful data insights. The role will primary be focussed around data format, data quality, data privacy, data sovereignty and defining the data standards that other areas (e.g. Stream Aligned teams) will follow. You will also be responsible for simplifying highly technical and complex information for nontechnical users to understand in the form of dashboards, data visualizations, regular and impromptu reports, and data querying tools for users to get the information they require.
Working as part of a platform team the Data Engineer role involves collaborating closely with everyone within the technology team and also the wider business (including data scientists, statisticians, cloud infrastructure engineers, developers, architects, analysts, product owners and the leadership team).

DATA ENGINEER JOB RESPONSIBILITIES:

When looking at the responsibilities can be broken down into the following:

• Ability to identify and implement internal improvements around scalability, optimal data delivery and automation capabilities.
• Develop a set of data guidelines and standards and support other teams in their usage and adoption.
• To develop, deploy and maintain BI tools and interfaces developing and maintaining custom visuals and dashboards that provide insights into key business metrics and trends that enhance the user experience and facilitate data exploration.
• Simplifying highly technical language and complex information and provide quantifiable solutions to complex data problems.
• Write and maintain queries and scripts to extract, transform and load data from various sources into various outputs conducting testing and validation to ensure quality, accuracy and reliability.
• Produce technical documents on database content and map various databases used in the organisation.
• Develop, design and analyse data architecture and data models that support efficient data processing and analysis.
• Ensure optimal performance of our data systems and platforms.
• Knowledge of (or experience) using CI/CD pipelines
• Collaborate with stakeholders to identify and define key performance indicators (KPIs) and data sources.