Data Platform Engineering Lead

Join us as a Data Platform 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 platform and framework 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 platform engineering community, you’ll deliver opportunities to support our strategic direction while building your network across the bank

What you'll do

We’ll look to you to demonstrate technical and people leadership to drive value for the customer through platform engineering, toolkit adoption, cloud integration, sourcing and data transformation frameworks. 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 platform engineers.

We’ll also expect you to be:

• Ensuring deployment and management of distributed data platforms
• Product licensing , adoption and integration
• Owning and Delivering the automation of data engineering pipelines
• Developing frameworks to enable bank’s data structures and metrics, advocating change where needed for product development
• Educating and embedding new tools and techniques into the business through role modelling, training and experiment design oversight
• Delivering platform roadmap and 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

We’re recruiting for multiple roles across a range to levels, up to and including experienced Managers.

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.

You’ll need experience in deploying and  managing distributed data/ETL pipelines (batch mode and real time streaming) hosted on Hadoop, Spark, Kafka, Informatica and MongoDB. You will also have experience of managing data engineering tooling/orchestration such as Streamsets and Informatica PWC/BDM/IICS on premise/cloud infrastructure. You will also demonstrate:

• Experience of developing real time data streaming pipelines using Change Data Capture (CDC), Kafka and Streamsets/NiFi/Flume/Flink
• Experience with Change Data Capture tooling such as IBM Infosphere, Oracle Golden Gate, Attunity, Debezium
• Experience of ETL technical design, automated data quality testing, QA and documentation, data warehousing, data modelling and data wrangling
• Expertise in Unix and DevOps automation tools like Terraform and Puppet and experience in deploying applications to at least one of the major public cloud provider such AWS, GCP or Azure
• Extensive experience using RDMS and one of the no-sql database such as MongoDB, ETL pipelines, Python, Java APIs using spring boot and writing complex SQLs
• A good understanding of cloud warehouse such as Snowflake
• A good understanding of modern code development practices
• Good critical thinking and proven problem solving abilities