Barclays-posted 3 months ago
Mid Level
Whippany, NJ
Credit Intermediation and Related Activities

Embark on a transformative journey as a Data Analytics Engineer. At Barclays, our vision is clear -to redefine the future of banking and help craft innovative solutions. We are seeking a skilled Data Analytics Engineer to transform complex data sets into actionable insights that drive business decisions. In this role, you will design, build, and maintain data pipelines and analytics solutions while collaborating with cross-functional teams to understand business requirements and deliver data-driven solutions. The purpose of the role is to build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure.

  • Build and maintain data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
  • Design and implement data warehouses and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
  • Develop processing and analysis algorithms fit for the intended data complexity and volumes.
  • Collaborate with data scientists to build and deploy machine learning models.
  • Professional programming experience in Java or Python alongside building production-grade data systems.
  • Advanced knowledge of RDBMS/NoSQL databases, data modeling, and modern Data Warehouse architectures.
  • Proven experience with AWS data services ecosystem (Glue, Redshift, Lambda, S3, EMR, Kinesis).
  • Expert-level experience with batch processing, stream processing, and data integration using big data frameworks like Spark, Flink, or Kafka Streams.
  • Advanced knowledge of data visualization tools like Tableau, SAP BO, or Power BI.
  • Expertise in containerization using Docker and Kubernetes for data workloads.
  • Experience with Infrastructure as Code (Terraform, CloudFormation).
  • Demonstrated success implementing serverless architectures for data processing.
  • Experience with DataOps and CI/CD pipelines for data solutions.
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