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AWS Data Engineer

Adecco UK Limited
7 months ago
Applications closed

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Senior AWS Data Engineer

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Data Engineer Python Spark ETL

Data Engineer (SC Clearance)

Data Engineer

AWS Data Engineer x 5

UK Wide

£50,000 - £90,000

Due to the nature of the clients supported we will require applicants to either hold current SC clearance or be eligible for SC clearance thus meaning living in the UK for the past 5 years.

A leading consultancy practice is currently looking to recruit x5 AWS Data Engineers to join their cloud data platforms team. You will work with colleagues with a range of skill sets to drive their customers digital and data transformation journey using the modern AWS cloud platform.

Your Role

  • Design and Develop Data Pipelines: Create robust pipelines to ingest, process, and transform data, ensuring it is ready for analytics and reporting.
  • Implement ETL/ELT Processes: Develop Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) workflows to seamlessly move data from source systems to Data Warehouses, Data Lakes, and Lake Houses using Open Source and AWS tools.
  • Adopt DevOps Practices: Utilize DevOps methodologies and tools for continuous integration and deployment (CI/CD), infrastructure as code (IaC), and automation to streamline and enhance our data engineering processes.
  • Design Data Solutions: Leverage your analytical skills to design innovative data solutions that address complex business requirements and drive decision-making.



Your Skills and Experience

  • Proficiency with AWS Tools: Demonstrable experience using AWS Glue, AWS Lambda, Amazon Kinesis, Amazon EMR , Amazon Athena, Amazon DynamoDB, Amazon Cloudwatch, Amazon SNS and AWS Step Functions.
  • Programming Skills: Strong experience with modern programming languages such as Python, Java, and Scala.
  • Expertise in Data Storage Technologies: In-depth knowledge of Data Warehouse, Database technologies, and Big Data Eco-system technologies such as AWS Redshift, AWS RDS, and Hadoop.
  • Experience with AWS Data Lakes: Proven experience working with AWS data lakes on AWS S3 to store and process both structured and unstructured data sets.
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