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Senior Data Engineer

2 months ago

London, Greater London, United Kingdom Salt Full time
About the Role

We are seeking a highly skilled Data Engineer to join our team at Salt, a leading company in the finance industry. As a Data Engineer, you will play a critical role in designing and implementing data engineering solutions on AWS, leveraging cloud DevOps and big data administration expertise.

Key Responsibilities
  • Cloud DevOps & Big Data Administration:
    • Manage and optimize big data environments on AWS, ensuring efficient administration and maintenance.
    • Leverage AWS Lake Formation to design and implement data lakehouses versus data fabric architectures, ensuring data integrity and accessibility.
  • Data Engineering & Spark Management:
    • Develop and maintain Spark jobs, focusing on auditing, monitoring, and instrumentation to ensure reliability and performance.
    • Perform Spark performance tuning, including understanding and applying Spark 3+ features, such as Adaptive Query Execution (AQE) and job-level resource management.
  • Infrastructure as Code (IaC):
    • Utilize Terraform for infrastructure provisioning and management, ensuring scalable and secure environments.
  • Data Storage & Management:
    • Work with data storage formats like Parquet and Hudi to optimize data storage and retrieval.
    • Implement and manage IAM policies for secure data access and management across AWS services.
  • Collaboration & Continuous Improvement:
    • Collaborate with cross-functional teams, including data scientists, analysts, and other engineers, to develop and deploy data solutions.
    • Continuously improve data engineering practices, leveraging new tools and techniques to enhance performance and efficiency.
Requirements
  • Cloud DevOps & Big Data:
    • Extensive experience in cloud DevOps and big data administration on AWS.
    • Proficiency in AWS Lake Formation, with a strong understanding of data lakehouse versus data fabric concepts.
  • Programming & Data Engineering:
    • Expertise in Python for data processing and automation.
    • Deep knowledge of Spark internals (Spark 3+ features), including architecture, events, system metrics, AQE, and job-level resource management.
  • Tech Stack:
    • Strong hands-on experience with Terraform for infrastructure management.
    • Experience with data formats such as Hudi and Parquet.
    • Familiarity with AWS Glue, HIVE, and IAM for data management and security.
Good to Have
  • Additional Tools & Technologies:
    • Knowledge of Iceberg and its application in data storage and management.
    • Experience with Airflow for workflow automation.
    • Familiarity with Terragrunt for managing Terraform configurations.
    • Understanding of DynamoDB and its integration within data environments.