Hybrid Full Stack Data Engineer

Posted last month

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About the role

  • Deliver audit-ready and traceable solutions to support assurance, compliance reviews, and fraud risk monitoring.
  • Develop and deploy data models that align with diverse business requirements across compliance, audit, fraud detection, and assurance.
  • Design, develop, and maintain data pipelines for collecting, transforming, and loading data into various data stores.
  • Build and maintain data warehousing and data lake solutions
  • Develop and deploy data models that support various business requirements
  • Write efficient and scalable code in languages such as Python, Scala, or Java
  • Lead the design of data solutions with quality, automation, and performance in mind
  • Own the data pipelines feeding into the Data Platform ensuring they are reliable and scalable
  • Ensure data is available in a fit-for-purpose and timely manner for business and analytics consumption
  • Work with Data Governance team to ensure solutions are compliant with regulations such as GDPR and CISO policies and data quality is baked-in to pipelines
  • Collaborate with cross-functional teams to understand data requirements and provide support for data-driven initiatives
  • Set and embed standards for systems and solutions, and share knowledge to keep the team engaged and skilled in the latest technology
  • Prototype and adopt new approaches, driving innovation into the solutions
  • Support alignment of requirements and sources of data from line of business systems and other endpoints
  • Mentor and guide junior members of the team to help them get up to speed in a short amount of time
  • Communicate complex solutions in a clear and understandable way to both experts and non-experts.
  • Stay up-to-date with industry trends and technology advancements in data engineering.

Requirements

  • Extensive experience leading AWS and cloud data platform transformations
  • Proven track record of delivering large-scale data and analytical solutions in a cloud environment
  • Hands-on experience with end-to-end data pipeline implementation on AWS, including data preparation, extraction, transformation & loading, normalization, aggregation, warehousing, data lakes, and data governance
  • Expertise in developing Data Warehouses
  • In-depth understanding of modern data architecture such as Data Lake, Data Warehouse, Lakehouse, and Data Mesh
  • Strong knowledge of data architecture and data modelling practices
  • Familiarity with CI/CD driven data pipeline and infrastructure
  • Agile delivery approach using Scrum and Kanban methodologies
  • Innovative problem-solving skills and ability to provide clear recommendations
  • Experience managing and leading a small team of data engineers
  • Strong knowledge of how data drives analytical and reporting activities, including automated marketing and personalization capabilities

Benefits

  • Flexible working arrangements
  • Professional development opportunities

Job title

Full Stack Data Engineer

Job type

Experience level

Mid levelSenior

Salary

Not specified

Degree requirement

Bachelor's Degree

Location requirements

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