Lloyds Banking Group is the UK’s biggest Retail, Digital and Mobile bank with over 30 million customers and a huge responsibility to help Britain Prosper.

Artificial Intelligence, Data Science and Robotics are already playing a huge part in the Group’s further £3bn digitisation…

Our Chief Data and Analytics Office brings together Data Engineering, Data Science, Business Intelligence (BI) and Agile Delivery to build data solutions in areas such as customer segmentation, pricing, credit decisioning, commercial performance and fraud detection.

They’re also making good use of Cloud, to enable more data-led decisions and help the Group achieve its ambition to be a truly data driven bank.

We’re talking everything from helping build data science solutions around virtual smart agents, network threat detection, price optimisation and so many other fascinating areas.

And in joining our Data Engineering team you could have a very bright future at the pioneering edge of data-led innovation!

You’d be working within a team of pathfinders and trailblazers and routinely working with industry partners, from start-ups to industry giants, to advance our analytics and data science agenda at pace.

And with your skills spanning across data mining/ analysis/ modelling and modern data platforms (e.g. Hadoop, Spark, Kafka, GCP, Azure) you’ll find yourself working on a range of very high-profile projects.

Together we’ll make it possible…

About the role:

We’re a multi-functional team, collaborating closely across numerous teams to solve some of the Bank’s toughest business problems.

We want to grow our team of data engineers who analyse data and build pipelines in distributed environments using Python, SQL and a wealth of other data technologies.

You’ll provide the much-needed ‘data expertise’ to help shape the approach to solving the problem and contributing new/ interesting datasets into the mix.

You’ll develop high quality, reusable data pipelines at scale, ingesting structured and unstructured data into our data lake.

You’d collaborate regularly with Machine Learning Engineers and Data Scientists while working in our Hadoop, Spark, Teradata, GCP and Azure environments.

So you’ll need to show a genuine passion for developing new solutions, evaluating new tech and translating data into analytics based opportunities – role-modelling Data Engineering as it should be in the new digital age.

Do you have the essential experience we’re seeking?

  • Good coding/ scripting experience using Python and SQL developed in a commercial/ industry setting

  • Computer science fundamentals: a clear understanding of data structures, algorithms, software design, design patterns and core programming concepts

  • Experience delivering analytical use cases in a cloud based environment

And experience in these would be a bonus:

  • Exposure to Hadoop technologies (e.g. HDFS, Hive, HBase) or prior experience working with high volume, low latency data storage and analytics platforms

  • Exposure to GCP cloud tooling (e.g. Cloud DataFlow, BigQuery)

What you’d get in return:

Our function is full of down-to-earth people passionate about data and sharing their expertise. And as Data underpins so many important initiatives it’s an area with huge career potential as well as offering you horizon-expanding exposure to a host of wider technologies.

Offering hybrid working patterns (2-3 days in either our London or Bristol hub) we believe that a healthy work/ life balance is as important as the work we deliver, just let us know what might work for you…

We’re also passionate about diversity and equal opportunity with industry recognition across gender, ethnicity, disability, LGBTQ+ and families. And, being disability positive, reasonable adjustments can be accommodated in our Recruitment process.

We’re simply committed to building an inclusive environment where all our colleagues can be themselves and succeed on merit.

We’ll also offer you a comprehensive package that includes:

  • A salary range between £48,000 – £80,000, depending on location and experience

  • Discretionary annual group performance bonus

  • Generous pension contribution of up to 15%

  • A 4% flex cash pot to spend on lifestyle benefits (or take as cash)

  • 30 days holiday plus bank holidays

  • Private Health cover you can extend to family members

  • Share schemes, including free shares

  • Generous parental/ adoption leave policies

So if you possess the Data Engineering skills we’re after then get in touch, we’d love to hear from you!…

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