Data Integration Engineer

 Posted 3 months ago
  
 India
  
2-5 years experience
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AI Summary

The engineer will be responsible for onboarding customers to Risk Adjustment workflow applications by designing and developing data flows, extraction processes, and integrating client data into these workflows. This role involves building and scaling automation, redefining data strategy, and working with relational databases and Python jobs.

Overview

Edifecs/Cotiviti is seeking a Data Integration Engineer to join our innovative software teams. In this position, you will be responsible for onboarding customers to the Risk Adjustment workflow applications. As part of this role, you will work with platform engineering, product, and implementation teams. The ideal candidate has experience in building scalable data pipelines that enable workflow applications, reporting, and customer confidence. You must have strong, hands-on technical expertise in big data technologies and communication abilities with non-tech and technical audiences.

Responsibilities

  • Design and develop data flows and extraction processes.
  • Integrate client’s data into the Edifecs/Cotiviti Risk Adjustment Workflows.
  • Work with relational databases and Python jobs.
  • Implement open-source standards for data quality.
  • Develop a new framework for data ELT jobs to scale implementation, monitoring, and quality.
  • Build and scale automation that orchestrate complex workflows.
  • Ability to support existing processes while leading efforts to redefine the data strategy.

Qualifications

  •  3+ years of hands-on experience with relational database systems (PostgreSQL).
  • 2+ years of hands-on experience developing ELT jobs/data pipelines within various technologies such as: Argo Workflows, cron, Airflow, dbt, great expectations.
  • 2+ years of experience in Linux system.
  • Proficiency in shell scripting and automation.
  • Experience building reusable data methods and working with version control systems (git).
  • 3+ years of hands-on experience with programming languages such as python.
  • Plus - Experience with container deployment platforms and tools, such as Kubernetes, Docker, Helm, and Terraform.
  • Plus - AWS Cloud experience: EC2, RDS, SQS, IAM, S3.

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