Data Pipeline Engineering Specialist designing and operating data pipelines for cybersecurity analytics at Morgan Stanley. Collaborating with stakeholders and ensuring performance and reliability of infrastructure.
Responsibilities
Collaborate with cyber security stakeholders (security response, investigations, insider threat) to onboard and integrate new data sources
Design and implement data mapping, transformation, and routing processes aligned to analytics and monitoring needs
Build and maintain integrations across cloud and on-premises cyber systems
Develop automation tools leveraging internal configuration management frameworks and APIs
Monitor, maintain, and optimize the performance, reliability, and scalability of data pipeline infrastructure
Act as a senior escalation point for complex troubleshooting, partnering with infrastructure teams to resolve issues
Produce and maintain detailed documentation for architecture, integrations, and operational processes
Requirements
Hands-on experience with large-scale dataflow platforms (Cribl, Logstash, Apache NiFi) and integrating data pipelines across cloud platforms (AWS, Azure, Google Cloud) and on-prem systems
Strong experience in field extraction, validation, and data parsing/normalization (regular expressions, Elasticsearch, Elastic Common Schema – ECS)
Solid understanding of operating systems and networking (Linux/Unix, HTTP, encryption)
Experience with distributed event streaming platforms (Apache Kafka, AWS Kinesis, Google Pub/Sub, MQ)
DevOps experience with tools such as Git, Jenkins, and Jira
Automation and infrastructure scripting using Python and Ansible
Understanding of cybersecurity data, event types, and monitoring requirements
Familiarity with Agile methodologies, particularly Kanban
Strong analytical thinking, advanced troubleshooting capabilities, and excellent verbal and written communication skills
Benefits
Employee benefits and perks that are comprehensive and attractive
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