Job Introduction
BPP Education is entering a new phase of its growth and evolution, attracting thousands more students each year and expanding into new verticals and new markets globally. The BPP Product & Technology (P&T) organisation is evolving rapidly, and driving transformation of its platforms, digital products and experiences, in order to help BPP Education scale and meet the growth of the business in the coming years.
We’re looking for an engineer to help us build and grow our Data Engineering team across all BPP’s platforms, products and user experiences. The Data Engineering team will enable BPP to leverage data, to inform and optimise how we deliver scalable, secure and performant experiences that delight and engage learners during their time studying with BPP and beyond, throughout their working lives.
As a Data Engineer, you will report to the Data Engineering Manager. Collaborating closely with teams across BPP P&T department (Data, Product Management, Product Design & Engineering), you will help deliver and evolve BPP Education’s vision to become more customer centred, design and data informed, to build products that meet and exceed our users’ needs across our education ecosystem.
Key responsibilities
- Run data pipelines to extract data from various source systems (log files, APIs, databases) and load them into our data lake / data warehouse confidentially using modern data tools and technologies
- Transform data into highly accessible and usable structures (tables)
- Design data solutions with clear metrics, dimensions, and organised into beautiful and well documented data marts or data meshes that analytics or data products / engineering teams find a joy to use.
- Responsible for robust testing practises and continuous optimisation, understanding that leveraging different testing methodologies is key to delivering a high quality product to our customers at pace. Pro-actively inputting into testing processes.
- Identify root cause of any production issues and make recommendations on robust and timely solutions. Ensuring that those recommendations are implemented across multiple solutions and designs where appropriate.
- Capture data requirements from across P&T, and question and understand why / what problems people are trying to solve with data so successful data engineering solutions can be communicated and built
- Care deeply about the integrity of the data your team manages and applying proactive and common-sense approaches to validating data quality, enabling effective usage of the data sources. Proactively inputting into data quality frameworks.
- Holistically look across the delivery of the team and ensure that all solutions are joined up and are being delivered in the best way to compliment all outputs.
- Apply security and protect privacy of all data following data governance policies at all time
- Develop and mentor others in the team on best practises and enhanced ways of working, always looking for new industry advancements that you can bring back into the team.
Essential Skills
- Proven experience as a Data Engineer
- Well versed in the following: cloud-based data storage solutions, data lakes, customer data platforms. (Python, Spark, SQL, Cloud Data Environments such as AWS, GCP, Azure)
- Good understanding of data modelling methods and data partitioning and compaction methods in Data Lake
- Experience of working with event driven architectures or real time streaming analytics
- Confident in writing and reading code in multiple languages
- Possess a deep understanding of how to translate product and business goals into data technology solutions.
- Demonstrable experience of working in Agile environments and more importantly an Agile culture and ethos
- Passionate about what you do and have a high interest in keeping up with current best practices in your areas of expertise.
- As a great influencer with great communication skills, you love sharing your knowledge with others and helping them grow.
- Experience in AWS data solutions
Desired Skills
- Experience in BPP technology;
- Spark (Python/Scala)
- Snowflake
- Salesforce CDP
- AWS
- AWS Lakeformation
- AWS Kinesis
- AWS Event Bridge
- Glue/Glue Data Brew
- App Flow
- NOSQL Databases e.g. DynamoDB
- SQL Databases e.g. MySQL