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Udacity · 6 hours ago

(Independent Contractor): Content Maintenance Mentor- Data Engineering

United States

Contract

Remote

Senior Level

Udacity, now an Accenture company, is on a mission to transform tech talent through innovative online learning. The Content Maintenance Mentor for Data Engineering will work with contractors to ensure course content remains current and aligned with industry standards, focusing on maintaining and updating data engineering courses and tools.

Artificial Intelligence (AI)E-LearningEdTechEducationMachine LearningRoboticsSoftwareTraining

Comp. & Benefits

No H1B

Responsibilities

Install and update data science and data engineering toolchains in existing workspace images (e.g., Python, R, Jupyter, VS Code extensions, CLI tools such as AWS CLI, Azure CLI, Kafka/Spark tooling)

Create new Docker images for Udacity Workspaces tailored to data workloads. This may require:

Writing and maintaining Dockerfiles, Makefiles, and shell scripts

Optimizing images for performance, reproducibility, and reliability

Coordinating with platform teams when changes affect Kubernetes/GKE configuration

Update IAM policies, RBAC configurations, and resource provisioning scripts as needed to support data workloads (e.g., access to S3/ADLS, Redshift/Synapse, Databricks, Kafka, managed databases)

Create or update Cloud Labs using our partner tools. This will require knowledge of AWS Policies, Azure RBAC, and Infrastructure as Code (Terraform, CloudFormation, or Bicep)

Create and maintain images or templates (e.g., AMIs, VM images, Databricks clusters) pre-loaded with required tools, drivers, and configurations for data projects

Install and configure tools in Linux environments (e.g., Python data stacks, Spark, Kafka clients, database clients) for student use

Develop Infrastructure as Code templates to automate provisioning of data infrastructure for exercises and projects (pipelines, data stores, compute, networking, monitoring)

Qualification

Data EngineeringAWSAzureInfrastructure as CodeDockerKubernetesCloud SecurityLinux AdministrationCI/CD PipelinesAutomation SkillsSoft Skills

Required

Deep expertise with data engineering and data platforms on AWS and/or Azure, including:

Advanced knowledge of Infrastructure as Code tools (Terraform, CloudFormation, or Bicep) for provisioning data infrastructure

Strong experience writing Dockerfiles, Makefiles, and shell scripts, especially for data science and data engineering environments

Hands-on experience with Kubernetes or container orchestration (GKE or equivalent) is a strong plus

Deep understanding of cloud security and data governance, including IAM policies, Azure RBAC, network controls, encryption, and handling of sensitive data

Proven ability to create and configure images and environments (e.g., AMIs, VM images, cluster templates, workspace images) for data workloads

Experience with Linux system administration and package management

Proficiency in setting up and configuring development environments and toolchains for data teams (Python/R environments, SQL engines, CLI tools, etc.)

Strong automation skills and ability to build reproducible infrastructure and environments

Experience with CI/CD pipelines and deployment automation (e.g., GitHub Actions, CircleCI, Azure DevOps) is a plus