DataOps Support Engineer

19 Hours ago • All levels • DevOps • Administrative

About the job

SummaryBy Outscal

Must have:
  • Troubleshooting and support experience
  • Data management and incident management
  • Jira and Collibra familiarity
  • Data pipeline issue resolution
  • SLA adherence and quick decision-making
Good to have:
  • AWS experience
  • Packer, Docker, Vault
  • ELK stack, Prometheus, Alert Manager
  • Kubernetes/Docker, Terraform
  • GoLang scripting
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Description

Position at Apexon

Company Description: Apexon is a digital-first technology services firm backed by Goldman Sachs Asset Management and Everstone Capital. We specialize in accelerating business transformation and delivering human-centric digital experiences. For over 17 years, Apexon has been meeting customers wherever they are in the digital lifecycle and helping them outperform their competition through speed and innovation.

 

DataOps support Engineer

Roles & Responsibilities: Overall, the ideal candidate for this Data Ops role should possess a combination of technical expertise, strong communication skills, problem-solving abilities, and experience in incident management. Monitoring Long Running/Hung or Failed Jobs in CDQ Product team. Collaboration with developers/Engineering teams to address platform-related issues, including code-related issues or resource constraints causing job stalls. Addressing email delivery failures or alert configuration issues. Ensuring efficient scheduling of data quality jobs. Managing all communication with stakeholders necessary to resolve support tickets. Resolving support tickets within specified Service Level Agreements (SLAs). Coordinating and tracking ticket escalations as needed. Maintaining support tickets in Jira. Contributing frequently asked questions to the Collibra knowledge base. Participating in on-call rotations for support coverage Technical Skills# Troubleshooting and support experience. Data management and incident management proficiency. Familiarity with JIRA and Collibra. Understanding data structures, flows, and quality concepts. Ability to identify and resolve data pipeline issues. Quick decision-making skills, especially for SLA adherence. Adaptability to handle changing priorities. Effective stakeholder management. Strong documentation abilities. Have experience, Knowledge on the following technologies.  AWS experience, Packer, Docker, Vault, ELK stack, Prometheus, Alert Manager,  Kubernetes/Docker, Terraform  Scripting/coding experience – ideally GoLang, Ubuntu OS/BottleRocket, Jenkins/GitLab/BitBucket

 

Disclaimer:We are an Equal Opportunity Employer (EOE). You can read our job applicant privacy policy here .

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