Engineering - Dallas - Associate, Security Engineering - 10427751

About the role

Design, develop, and maintain scalable data ingestion and processing pipelines to collect, transform, enrich, and load large volumes of structured and semi-structured data from diverse sources into a centralized big data platform. This enables the organization to detect and analyze malicious cyber threats and anomalous activity across its infrastructure.

Responsibilities

• Develop and optimize both batch and streaming data processing workflows to ensure timely and reliable delivery of security event data and telemetry to downstream analytics systems, supporting real-time alerting and incident response capabilities.
• Design and implement data models, schemas, and data warehouse structures to organize and correlate high-volume event data from multiple sources, supporting analytical reporting, data science initiatives, and operational decision-making.
• Build and maintain data quality monitoring frameworks, alerting systems, and observability dashboards to ensure pipeline reliability, accuracy, completeness, and performance, guaranteeing that critical data streams remain uninterrupted for continuous monitoring.
• Develop and maintain Continuous Integration and Continuous Deployment (CI/CD) pipelines to automate the testing, building, and deployment of data engineering applications and infrastructure components, ensuring rapid and reliable delivery of platform updates.
• Deploy, administer, and scale data systems and infrastructure across on-premises data centers and Amazon Web Services (AWS) cloud environments using container orchestration tools such as Kubernetes to support high-availability, fault-tolerant data processing at scale.
• Research, evaluate, and implement best-in-class data engineering tools and technologies by conducting Proof-of-Concept activities and recommending solutions that improve platform capabilities, scalability, and efficiency.
• Collaborate with cross-functional teams — including threat management, detection engineering, data science, and analytics teams — to gather data requirements, define data contracts, and ensure data streams are effectively configured and monitored.
• Coordinate with product owners and third-party vendor support teams to elicit technical requirements and resolve platform issues.
• Participate in architecture and design discussions to develop solutions that advance the organization's data infrastructure and analytical maturity for processing and analyzing large-scale enterprise telemetry data.

Requirements

• Master’s degree (U.S. or foreign equivalent) in Cyber Security, Computer Engineering, Data Science and Analytics, or a related field and one (1) year of experience in the job offered or a related security or data engineering role.
• Alternatively, a Bachelor’s degree (U.S. or foreign equivalent) in Cyber Security, Computer Engineering, Data Science and Analytics, or a related field and three (3) years of experience in the job offered or a related security or data engineering role.

Qualifications

Prior work experience must include:

• One (1) year of experience (with a Master’s degree) or three (3) years of experience (with a Bachelor’s degree) designing, deploying, and maintaining data pipeline systems and ingestion frameworks across on-premise and cloud environments.
• One (1) year of experience (with a Master’s degree) or three (3) years of experience (with a Bachelor’s degree) implementing and supporting distributed data technologies such as Spark, Kafka, Kubernetes, and BigQuery or similar for real-time and batch data processing and analysis.
• One (1) year of experience (with a Master’s degree) or three (3) years of experience (with a Bachelor’s degree) developing automation and tooling using Python to support data monitoring, enrichment, and platform engineering workflows.
• One (1) year of experience (with a Master’s degree) or three (3) years of experience (with a Bachelor’s degree) building and supporting ETL and data ingestion pipelines to centralize large-scale event data into scalable big data infrastructure.
• One (1) year of experience (with a Master’s degree) or three (3) years of experience (with a Bachelor’s degree) implementing and administering AWS cloud infrastructure to enable reliable data processing and analytics capabilities.
• One (1) year of experience (with a Master’s degree) or three (3) years of experience (with a Bachelor’s degree) collaborating cross-functionally with engineering, analytics, and data science teams to ensure systems and data streams are effectively configured and monitored.