Data Engineer

Join us as a Data Engineering Lead

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’s data 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 demonstrate technical and people leadership 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, leading a team of data engineers.

We’ll Also Expect You To Be

Working with Data Scientists and Analytics Labs to translate analytical model code to well tested production ready code

Helping to define common coding standards and model monitoring performance best practices

Owning and 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

Leading and delivering data engineering strategies to build a scalable data architecture and customer feature rich dataset for data scientists

Leading and 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 an expert level 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 extensive experience in extracting value and features from large scale data.

We'll also expect you to have knowledge of of big data platforms like Snowflake, AWS Redshift, Postgres, MongoDB, Neo4J and Hadoop, along with good knowledge of cloud technologies such as Amazon Web Services, Google Cloud Platform and Microsoft Azure

You’ll Also Demonstrate

Knowledge of core computer science concepts such as common data structures and algorithms, profiling or optimisation

An understanding of machine-learning, information retrieval or recommendation systems

Good working knowledge of CICD tools

Knowledge of programming languages in data engineering such as Python or PySpark, SQL, Java, and Scala

An understanding of Apache Spark and ETL tools like Informatica PowerCenter, Informatica BDM or DEI, Stream Sets and Apache Airflow

Knowledge of messaging, event or streaming technology such as Apache Kafka

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, Hadoop and SQL