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Enterprise Data Architect

developrec
London
9 months ago
Applications closed

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As an Enterprise Data Architect, you will define and implement data strategies, ensuring seamless data flow, governance, and scalability. You will work closely with cross-functional teams to design data architectures that meet the demanding needs of the financial sector, with a strong focus on MongoDB and Kafka for high-volume data processing.


Your expertise in finance will be crucial in ensuring compliance, optimising data pipelines, and supporting critical business decisions.


Key Responsibilities

  • Design and implement scalable, high-performance enterprise data architectures within financial services
  • Develop and optimise MongoDB implementations for structured and semi-structured data storage
  • Architect and maintain Kafka-based real-time data streaming solutions for low-latency processing
  • Define and enforce data governance, security, and compliance best practices in alignment with financial regulations.
  • Collaborate with engineering, data science, and business teams to ensure efficient data integration and accessibility
  • Evaluate and recommend emerging technologies to enhance data processing capabilities
  • Lead architectural reviews, ensuring alignment with industry best practices and business objectives
  • Provide technical leadership, mentoring teams on data modelling, database optimisation, and event-driven architectures


Skills & Experience Required

  • Extensive experience in enterprise data architecture within the financial services industry
  • Strong expertise in MongoDB, including schema design, performance tuning, and indexing strategies
  • Hands-on experience with Kafka for real-time event-driven architectures
  • Deep understanding of data governance, security, and compliance in regulated environments
  • Strong proficiency in cloud-based architectures (AWS, GCP, or Azure)
  • Experience in designing scalable, distributed, and high-availability data solutions
  • Ability to communicate complex technical concepts to non-technical stakeholders
  • Experience with data lake and warehouse architectures
  • Familiarity with NoSQL and relational databases beyond MongoDB

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