C

Citi

Runs banking and payments for global clients

Data Platform Engineer - Cybersecurity Operations

Data EngineeringPosted on Nov 9
Full-timeIrving, TX, USAHybrid

About the Job

Requirements

  • A bachelor's degree, university degree, or equivalent experience is required.
  • Demonstrable expertise in data platform architecture and engineering, including architecting and operating large-scale, mission-critical data platforms and balancing scalability, cost, performance, and reliability.
  • Hands-on experience building and operating large-scale batch and streaming data pipelines using technologies such as Cribl, Kafka, Spark, Flink, Airflow, or equivalent.
  • Expertise in data lake and data warehouse architecture at enterprise scale, including foundational decisions about storage formats, partitioning strategies, and query engines; examples include Delta Lake, Iceberg, Snowflake, BigQuery, and Redshift.
  • Experience with cloud-native data infrastructure on AWS, Azure, or GCP, including storage tiering, cost optimization, and event-driven architectures.
  • Understanding of security telemetry, including logs, network flow, endpoint/EDR data, identity events, and cloud audit logs, and the challenges of ingesting and normalizing it at scale.
  • Advanced proficiency in a major programming language such as Python, Go, Java, or Scala for pipeline development and automation.
  • Experience with schema design, data modeling, and metadata management for large, heterogeneous, high-velocity datasets.
  • Grounding in cybersecurity fundamentals, particularly SOC/OSVM operations, log management, and detection and analytics use cases.
  • Experience with relational, NoSQL, time-series, and columnar/analytical database technologies.
  • Software engineering fundamentals including CI/CD, infrastructure-as-code, version control, automated testing, and observability/monitoring practices.
  • Ability to architect for scale and reliability in mission-critical, 24x7 operational environments.
  • Ability to collaborate across security operations, detection engineering, and data science teams.

Responsibilities

  • Design, build, and operate scalable, resilient, high-throughput batch and streaming data pipelines that ingest enterprise security telemetry, including logs, alerts, network flow data, endpoint events, identity signals, and cloud events.
  • Develop normalization and enrichment logic to transform heterogeneous SOC telemetry formats into standardized schemas for downstream analytics and detection platforms.
  • Architect and maintain the storage backbone, including data lakes, warehouses, and streaming stores, as the durable, queryable source of truth for SOC data at enterprise scale.
  • Build and operate data lake infrastructure optimized for high-volume security telemetry, balancing cost, performance, retention, and query flexibility.
  • Ensure low-latency delivery of normalized SOC data to analytics platforms, SIEM/XDR tooling, and other downstream systems.
  • Tune pipeline throughput, storage partitioning, and query performance as telemetry volumes and analytics demands evolve.
  • Implement monitoring, alerting, and self-healing capabilities to ensure pipeline uptime, data completeness, and data quality at production scale.
  • Define and enforce data schemas, taxonomies, and metadata standards across ingested telemetry sources.
  • Build reusable frameworks and automation to onboard new telemetry sources as the tool and sensor ecosystem expands.
  • Ensure secure handling, encryption, access control, and regulatory compliance for sensitive security data throughout its lifecycle.
  • Partner with cybersecurity operations analysts, detection engineers, threat and exposure management teams, and data science teams to meet operational and analytical needs.
  • Maintain architecture documentation, data dictionaries, and operational runbooks.

Desired Qualifications

  • 10 or more years of experience architecting data platforms specifically for SOC, SIEM, or XDR environments.
  • Familiarity with AI/ML pipeline requirements, including feature stores and training data pipelines, for advanced security analytics.
  • Experience with open table formats such as Iceberg, Delta Lake, and Hudi, and modern lakehouse architectures.
  • A master's degree.
  • Relevant certifications, such as cloud data engineering certifications or GIAC, although certifications are not required in lieu of hands-on expertise.

About the Company

Citi

Runs banking and payments for global clients

Citi runs banking, investment and payment services for companies, governments and individuals around the world. Its global network connects institutions with local banking systems, while its US consumer business sells credit cards and deposit accounts. Corporate clients use Citi to manage cash, finance trade and raise capital, and investors use its trading, custody and wealth services to hold and manage assets. The bank earns interest on loans and fees from payments, securities transactions, financial advice and account services. Citi traces its banking roots to 1812; the Citigroup holding company was formed in 1998, and its headquarters are in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1812

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