Join us as a Data Platform Engineer
- This is an exciting opportunity to use your technical expertise to collaborate with colleagues and build effortless, digital first customer experiences
- You’ll be simplifying the bank through developing innovative data driven solutions, inspiring to be commercially successful through insight, and keeping our customers and the bank safe and secure
- Participating actively in the data engineering community, you’ll deliver opportunities to support our strategic direction while building your network across the bank
- We’re recruiting for multiple roles across a range to levels, up to and including experienced managers
What you'll do
We’ll look to you to drive value for the customer through modelling, sourcing and data transformation. You’ll be working closely with core technology and architecture teams to deliver strategic data solutions, while driving Agile and DevOps adoption in the delivery of data engineering.
We’ll also expect you to be:
- Delivering the automation of data engineering pipelines through the removal of manual stages
- Developing comprehensive knowledge of the bank’s data structures and metrics, advocating change where needed for product development
- Educating and embedding new data techniques into the business through role modelling, training and experiment design oversight
- Delivering data engineering strategies to build a scalable data architecture and customer feature rich dataset for data scientists
- Developing solutions for streaming data ingestion and transformations in line with streaming strategy
The skills you'll need
To be successful in this role, you’ll need to be a programmer and Data Engineer with a qualification in Computer Science or Software Engineering. You’ll also need a strong understanding of data usage and dependencies with wider teams and the end customer, as well as a proven track record in extracting value and features from large scale data.
You’ll need experience of deploying and managing distributed data platforms such as Spark, Hadoop, Kafka, MongoDB and Neo4J. And you’ll also have experience of managing data science and engineering tooling on the cloud such as Sage Maker, ML Ops, Airflow, Stream Sets and Informatica.
You’ll also demonstrate:
- Experience in deploying applications to at least one major public cloud provider such as Amazon Web Services, Azure or Google Cloud Platform
- Expertise in Unix and DevOps automation tools like Terraform and Puppet
- Knowledge and experience of architecting on the cloud using site reliability engineering and security principles
- Experience of ETL technical design, automated data quality testing, QA and documentation, data warehousing, data modelling and data wrangling
- Extensive experience using RDMS, ETL pipelines, Python and SQL
- A good understanding of modern code development practices
- Good critical thinking and proven problem solving abilities