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Data Engineering Lead

eFinancialCareers
Job LocationLondon
EducationNot Mentioned
SalaryCompetitive salary
IndustryNot Mentioned
Functional AreaNot Mentioned
Job TypePermanent , full-time

Job Description

Join us as a Data Engineering Lead

  • This is an exciting opportunity to lead a talented team of data engineers and scientists
  • Youll 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, youll deliver opportunities to support our strategic direction while building your network across the bank
What youll doWell look to you to drive value for the customer through modelling, sourcing and data transformation. Youll be working closely with core technology and architecture teams to deliver strategic data solutions, while driving Agile and DevOps adoption in thedelivery of data engineering. Well also expect you to be:
  • Delivering the automation of data engineering pipelines through the removal of manual stages
  • Developing comprehensive knowledge of the banks 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 youll needTo be successful in this role, youll need to be a confident data engineering lead with strong people management and stakeholder management skills. Youll display critical thinking and problem solving ability, and will have worked in environments where thereare multiple data & analytics systems. Youll 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. Youll also demonstrate:
  • Excellent understanding of modern code development practices and cloud data solutions and principles
  • Experience of ETL technical design, automated data quality testing, QA and documentation, data warehousing, data modelling and data wrangling
  • Extensive experience of RDMS, ETL pipelines, Python, Hadoop and SQL, Pyspark and Synapse
  • Experience of Azure Data Lake, Azure Data Factory, Databricks is highly desirable
  • Experience of maintaining ML models, ML OPs Pipelines and model factory
  • An awareness of de-centralized data architectures

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