DataOps Engineer

This is a remote position.

• Design, develop, and maintain data pipelines to extract data from various sources, populating data lakes and data warehouses.
  
• Develop and implement data transformation rules.
  
• Collaborate with Product Analysts, Data Scientists, and Engineers to identify and transform data to make it more understandable and actionable.
  
• Work with the data governance team to implement data quality checks and maintain data catalogs.
  
• Utilize orchestration, logging, and monitoring tools to build resilient data pipelines.
  
• Apply test-driven development methodologies when building ELT/ETL pipelines.
  
• Analyze and interpret data to support business decision-making.
  
• Use Git for version control and implement various branching strategies.
  
• Contribute as an active member of an agile development team.
  
• Create and maintain comprehensive technical documentation.
  

Requirements

• 3-6 years of relevant experience in data engineering or a related field.
  
• Solid experience with AWS services: S3, IAM, Redshift, Sagemaker, Glue, Lambda, Step Functions, CloudWatch.
  
• Experience with data platforms such as Databricks and Dataiku.
  
• Proficiency in Python and/or Java.
  
• Strong knowledge of SQL, preferably with experience in Redshift.
  
• Experience with DevOps tools: Jenkins, CloudFormation, Terraform, Git, Docker.
  
• 2-3 years of experience with Spark, especially PySpark.
  
• Ability to work effectively in cross-functional teams and agile environments.
  

Benefits

• Location: Czechia
  
• Freelance
  
• Working for a global pharmaceutical leader.
  
• Long-term project.