Engineering - Dallas - Associate, Security Engineering - 10427751

Socket.dev; Dallas (TX); On-site; USD 120,000 - 170,000; Full time

Job summary

Goldman Sachs is seeking an Associate, Security Engineering in Dallas, TX, to design and maintain scalable data ingestion pipelines that collect, transform, enrich, and load large volumes of structured and semi-structured data from diverse sources into a centralized big data platform for threat detection and anomaly analysis.

The role includes building batch and streaming workflows for real‑time alerting, designing data models and warehouse structures, and establishing data quality monitoring,

Qualifications

• Master’s degree in Cyber Security, Computer Engineering, Data Science and Analytics, or related field with 1 year of experience
• Or Bachelor’s degree with 3 years of experience in security or data engineering
• Experience designing, deploying, and maintaining data pipeline systems across on‑prem and cloud environments

Responsibilities

• Design, develop, and maintain scalable data ingestion and processing pipelines for large volumes of data
• Build batch and streaming workflows for timely delivery of security event data
• Develop data models, schemas, and data warehouse structures for analytics
• Create data quality monitoring, alerting, and observability dashboards
• Develop CI/CD pipelines to automate testing, building, and deployment of data applications
• Scale data systems across on‑prem and AWS cloud with Kubernetes
• Collaborate with threat management, data science, and analytics teams
• Engage with product owners and vendors to elicit requirements and resolve issues
• Contribute to architecture discussions to improve data infrastructure

Skills

Data pipelines

Python

CI/CD

Collaboration

Education

Master’s degree in Cyber Security/Comp Eng/Data Science

Bachelor’s degree in Cyber Security/Comp Eng/Data Science

Tools

Kafka

Spark

Kubernetes

BigQuery

Python

Job description

Job Duties: Associate, Security Engineering with Goldman Sachs Services LLC in Dallas, Texas. 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, enabling the organization to detect and analyze malicious cyber threats and anomalous activity across its infrastructure. 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 theOrganization's data infrastructure and analytical maturity for processing and analyzing large-scale enterprise telemetry data.

Job 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 OR 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. 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) with each of the following: designing, deploying, and maintaining data pipeline systems and ingestion frameworks across on-premise and cloud environments; implementing and supporting distributed data technologies such as Spark, Kafka, Kubernetes, and BigQuery or similar for real-time and batch data processing and analysis; developing automation and tooling using Python to support data monitoring, enrichment, and platform engineering workflows; building and supporting ETL and data ingestion pipelines to centralize large-scale event data into scalable big data infrastructure; implementing and administering AWS cloud infrastructure to enable reliable data processing and analytics capabilities; and collaborating cross-functionally with engineering, analytics, and data science teams to ensure systems and data streams are effectively configured and monitored.

©The Goldman Sachs Group, Inc., 2026. All rights reserved. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veteran status, disability, or any other characteristic protected by applicable law.