Specialist I, DevOps Engineering

Key Responsibilities

• Infrastructure & Networking:
• Design and maintain a secure AWS environment within a Factory Account structure.
• Configure and manage Factory VPCs, Private Subnets, VPC Endpoints, and S3 Gateway Endpoints to ensure absolute network isolation and zero public internet exposure for backend data.
• Data Pipeline Orchestration:
• Build, optimize, and maintain event-driven data extraction pipelines utilizing AWS Step Functions and Lambda to orchestrate distributed Scrapy (Python) web-scraping workloads.
• Application Containerization & Deployment:
• Manage containerized applications using Amazon ECR.
• Support and maintain the hosting infrastructure for frontend Streamlit applications running within the AWS environment.
• Hybrid Cloud Integration:
• Collaborate with cross-functional teams to implement secure Single Sign-On (SSO) and user authentication utilizing Merck Azure AD.
• Maintain and optimize Azure Deployment Pipelines for robust CI/CD across environments.
• Security & Database Management:
• Manage relational databases via Amazon RDS and secure object storage using S3.
• Enforce strong security postures by centralizing credentials, API keys, and connection strings within AWS Secrets Manager.
• Monitoring & Observability:
• Implement comprehensive logging, tracking, and metrics across all containerized workloads, serverless functions, and network paths using Amazon CloudWatch.

Requirements & Tech Stack

• Amazon Web Services (AWS):
• Networking: Advanced knowledge of VPC architecture, Private Subnets, VPC Endpoints (PrivateLink), and S3 Gateway Endpoints.
• Compute & Orchestration: Deep expertise in AWS Lambda (Serverless) and AWS Step Functions for workflow state machine management.
• Storage & Databases: Hands-on experience with Amazon S3 and Amazon RDS administration.
• Security & Management: Proficient with AWS Secrets Manager, EventBridge (CloudWatch Events), and Amazon ECR.
• Observability: Strong experience setting up dashboards and alerts in Amazon CloudWatch.
• Azure & Hybrid Integration:
• Identity Management: Enterprise-level experience integrating applications with Azure AD for authentication/SSO.
• DevOps: Proven experience building and managing CI/CD automated workflows via Azure Deployment Pipelines.
• Data Engineering & AI/ML Development:
• Data Extraction: Strong familiarity with Python-based data extraction, specifically the Scrapy framework.
• AI/ML Concepts: Foundational understanding of hosting, scaling, and managing infrastructure for Machine Learning (ML) models and LLM Modules.
• Frontend UI: Experience deploying and supporting Streamlit applications.