Data Engineer with AWS @ AltexSoft

1 week ago

Remote, Czech Republic AltexSoft Full time
You Have
  • Strong experience with AWS DevOps practices for data infrastructure, including Security, Networking, and Monitoring. 
  • Expertise in building and managing AWS Data solutions focused on Analytical Applications. 
  • Experience with AWS Kinesis and Firehose to manage real-time data ingestion and streaming. 
  • Proficiency with AWS Glue for data transformation and AWS Athena for querying large datasets in S3. 
  • Expertise in managing and optimizing AWS Redshift for large-scale data warehousing and analytics. 
  • Strong experience with Apache Airflow for scheduling and orchestrating complex data pipelines. 
  • Strong proficiency in Python and PySpark for data transformations and distributed data processing. 
  • Solid experience with Unix and AWS Command Line for managing cloud environments and deploying data pipelines 
  • Basic knowledge of AWS CloudWatch for monitoring and troubleshooting data workflows 
Would be a plus
  • Familiarity with Terraform for automating the provisioning and management of infrastructure. 
  • Understanding of AWS Quicksight for creating visual dashboards and presenting data insights. 
  • Basic knowledge of AWS CloudWatch for monitoring and troubleshooting data workflows. 
  • Familiarity with AWS Lambda for event-driven data processing and automation. 

We are looking for an experienced Data Engineer with AWS experience to work on data infrastructure and analytical applications of our client. You’ll be part of a team dedicated to leveraging cloud technologies to enhance data processing and analytics capabilities. This position requires strong expertise in AWS services, DevOps practices, and advanced data engineering skills, focusing on building and managing data pipelines and infrastructure using AWS tools. Our customer is one of the leaders in the Travel market. They drive different digital solutions to make business travel easier and more effective.

,[Develop and maintain efficient data processing workflows to transform raw data into structured formats suitable for analysis. , Maintain, grow, and extend the existing data infrastructure so AWS can be leveraged for new data use cases in a secure and scalable manner. , Design and implement processes for collecting and consolidating data from various sources, including databases, APIs, and external feeds. , Support data analytics by developing pipelines and tools that allow data scientists and analysts to access and analyze data effectively. , Create and manage data models that define the structure, relationships, and flow of data within systems. , Define and implement optimal data structures to support the efficient storage and retrieval of data. , Connect with Development Teams and stay updated on relevant changes in the source data systems. ] Requirements: AWS, Cloud, DevOps, Data engineering, Data pipelines, Security, Networking, AWS Glue, AWS CloudWatch, Apache Airflow, Python, PySpark, Unix, Terraform, Use cases, Data analytics, Data structures, Storage Tools: Jira. Additionally: Small teams, International projects.

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