Data engineer in banking

Описание

Barclays is a banking and financial services organization that transforms complex data into strategic assets supporting innovation, regulatory compliance, advanced analytics, and AI.

• Build and maintain data architecture pipelines for transferring and processing durable, complete, and consistent data
• Design and implement data warehouses and data lakes that handle required data volumes and velocity while meeting security measures
• Develop processing and analysis algorithms for the intended data complexity and volumes
• Collaborate with data scientists to build and deploy machine learning models
• Contribute to or set strategy, drive requirements, and recommend changes
• Plan resources, budgets, and policies
• Manage and maintain policies and processes
• Deliver continuous improvements and escal...
• Guide technical direction as a subject matter expert within the discipline
• Lead collaborative, multi-year assignments
• Guide team members through structured assignments
• Identify when additional areas of specialization are needed
• Train, guide, and coach less experienced specialists
• Provide information affecting long-term profits, organizational risks, and strategic decisions
• Advise functional leadership teams and senior management on functional and cross-functional impacts and alignment
• Manage and mitigate risks through assessment in support of the control and governance agenda
• Demonstrate leadership and accountability for managing risk and strengthening controls
• Collaborate with other work areas to stay aligned with business activity and strategies
• Create solutions by comparing and selecting complex alternatives
• Apply extensive research to problem-solving processes
• Build and maintain trusting relationships and partnerships with internal and external stakeholders

• Experience with cloud data warehousing solutions such as Snowflake, Amazon Redshift, or AWS
• Understanding of data integration processes and tools such as Databricks, DBT, or Glue
• Ability to design data models aligned with ETL pipelines
• Understanding of data management standards, regulatory compliance including GDPR and HIPAA, and security protocols
• Deep knowledge of entity-relationship modeling, normalization and denormalization, and dimensional modeling
• Proficiency with data modeling tools such as erwin Data Modeler, SAP Power Designer, or ER/Studio
• Advanced SQL skills, including DDL and DML
• Ability to profile, analyze, and manipulate data in relational database management systems
• Ability to translate complex business requirements into structured, efficient, and scalable data models
• Ability to ensure data integrity and optimize database performance through indexing and partitioning
• Excellent verbal and written communication skills for explaining technical data concepts to non-technical stakeholders
• Experience working in agile teams with data engineers, architects, and business analysts
• Ability to demonstrate risk and controls, change and transformation, business acumen, strategic thinking, and digital and technology skills
• Nice to have:
  Experience guiding team members, training and coaching less experienced specialists, and advising senior stakeholders

Office role in Glasgow.