RRemoteville

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Mindex logoMindex

Data Engineer

Skills
Data EngineeringAWS CloudformationAWS GlueAWS LambdaAmazon RedshiftData PipelinesModel Selection
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • AS or BS degree in a related field or equivalent education
  • 3-5 years software development experience
  • Experience with analytics tools or programming languages (Python, R, Spark, Hadoop, etc.)
  • Experience with SQL and no-SQL databases
  • Experience with data visualization tools (Quicksight, Tableau, Power BI, etc.)
  • Experience building, testing, scaling, and maintaining Cloud-native data pipelines
  • Experience with OLTP and OLAP databases
  • Familiarity with DevOps tools like AWS CodePipeline, Azure DevOps, or GitLab
  • Experience with infrastructure as code using AWS CloudFormation and Terraform
  • Experience with serverless compute platforms like AWS Lambda and AWS Glue
  • Familiarity with AWS AI/ML services like Amazon Q, Bedrock, and Sagemaker
  • Strong communication skills
  • Strong analysis and problem-solving skills
  • Focus on customer service
  • Highly organized and accurate
  • Strong initiative and follow-through
  • Collaborative team environment competence
  • Ability to work independently but seek assistance when needed

Nice to have

  • Strong communication skills
  • Experience with data pipeline
  • Strong analysis
  • Customer service focus
  • Well organized
  • Strong initiative
  • Highly collaborative
  • Willingness to accept feedback
  • Ability to work independently

Day to day

  • Deliver data focused, cloud native software solutions to various clients
  • Provide input to architectural and software solutions inspired by project challenges
  • Engage directly with client stakeholders and complete project tasks aligning with client vision
  • Develop both technical and non-technical connections within the team, across Mindex delivery teams, and with customer stakeholders
  • Apply software development experience using analytics tools and/or programming languages, databases, or data visualization tools
  • Build, test, scale, and maintain Cloud-native data pipelines
  • Contribute to the design, execution, and successful delivery of large-scale, critical, or complex data solutions
  • Use DevOps tools and infrastructure as code for data engineering tasks
  • Utilize AWS AI/ML services for data engineering projects