C

Citi

Runs banking and payments for global clients

Java Big Data Engineering Lead Senior Vice President

Engineering LeadershipPosted on Nov 9
Full-timeRutherford, NJ, USA$176.7k - $265.1k

About the Job

Requirements

  • At least 10 years of software engineering experience, including extensive experience leading Java application development and engineering teams in a large-scale enterprise environment.
  • Deep expertise in Java, Spring Boot, Python, APIs, and microservices architectures.
  • Hands-on knowledge of building and scaling Big Data technologies including Spark, Kafka, the Hadoop ecosystem, Iceberg, Delta Lake, Databricks, Snowflake, and Trino.
  • Experience delivering high-volume, low-latency, mission-critical platforms in a regulated financial services environment.
  • Experience supporting AI and machine learning data pipelines, feature stores, and enterprise-scale analytics solutions.
  • Experience architecting high-performance, low-latency systems for trading, risk, or analytics platforms.
  • Experience driving cloud transformation, automation, and modernization programs across engineering organizations.
  • Experience leading and mentoring senior engineers, architects, and engineering managers.
  • Experience establishing engineering standards, architecture governance, and design review practices.
  • Experience partnering with business stakeholders to translate requirements into scalable data and analytics solutions.
  • A Bachelor's or university degree in a related field, or a Master's degree.

Responsibilities

  • Define and execute the engineering roadmap for Java, Python, cloud-native, and Big Data platforms to align technology delivery with business objectives.
  • Lead multiple engineering teams building Java applications, API platforms, microservices, and enterprise data services supporting trading, risk, and analytics workflows.
  • Architect high-performance, low-latency systems that keep critical trading and operational platforms reliable under heavy volume.
  • Build enterprise-scale Big Data ecosystems using Spark, Kafka, Flink, Hadoop, Iceberg, Delta Lake, Pinot, and Trino for real-time streaming and large-scale batch processing.
  • Partner with business stakeholders to enable advanced analytics, AI and machine learning initiatives, and regulatory reporting through data-driven platforms.
  • Set enterprise standards for data governance, lineage, metadata management, and data quality across engineering teams.
  • Champion modern engineering practices including DevSecOps, CI/CD automation, and observability to strengthen platform reliability.
  • Mentor senior engineers, architects, and engineering managers to build high-performing teams capable of delivering complex global programs.

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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