Über
Salary Range: $65/hr to $71/hr on W2
Introduction
An Analytics platform engineer supporting Azure Synapse and Azure Data Factory from a DevOps perspective requires a hybrid skill set spanning primarily cloud infrastructure management, automation, and CI/CD practices. It is helpful if they have a background or exposure to ELT, data engineering, and Database Administration Concepts. The resource will be responsible as an engineer on the Analytics Platform Engineering team where we deploy Synapse Analytics Workspaces and Azure Data Factory. They are responsible for the implementation for our internal teams as a PaaS offering and may support a CI/CD solution using a Custom GitLab to GitHub adapter/translator written in GoLang.
Required Skills & Qualifications 4 years of experience developing APIs and integrating with 3rd party APIs. Strong SQL skills (SQL Server or Oracle). Familiarity with scripting languages (Python, Bash, PowerShell). Experience with version control systems (Git, GitHub, GitLab). Knowledge of CI/CD pipelines and DevOps best practices. Excellent problem-solving, analytical, and communication skills. Azure AD, OAuth, JWT, Azure hands-on with AD B2C, BOT, SignalR, AKS, App Registrations, App Insights. Prior work experience at the client or in the client's industry. Applicants must be able to work directly for Artech on W2.
Data Engineering fundamentals: Strong understanding of ETL/ELT processes, data modeling, data warehousing, and big data concepts. Experience with containerization: Docker and container orchestration (Azure Kubernetes Service - AKS). Client Certified: Azure Data Engineer Associate (DP-203) or Client Certified: Azure DevOps Engineer Expert (AZ-400). Day-to-Day Responsibilities
Implement CI/CD Pipelines: Design and maintain continuous integration and continuous deployment pipelines using tools like Azure DevOps or GitHub Actions. Infrastructure as Code (IaC): Provision and manage Azure data services through code using tools such as Terraform, ARM templates, or Bicep. Platform Operations: Deploy, manage, and optimize Azure data services, including monitoring and troubleshooting data pipeline failures. Automation & Scripting: Automate routine operational tasks using scripting languages like Python, PowerShell, or Bash. Security & Compliance: Implement security best practices, including IAM, data encryption, and compliance with data governance policies. Collaboration: Work closely with data engineers, data scientists, and business analysts to translate data requirements into robust technical solutions. Company Benefits & Culture
Competitive hourly rate. Opportunities for professional growth and development. Collaborative and innovative work environment.
For immediate consideration please click APPLY to begin the screening process with Alex.
Sprachkenntnisse
- English
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