Applications Development Technology Lead Analyst

Citi • Jersey City, NJ

1d • Onsite

About The Position

The Applications Development Technology Lead Analyst is a senior level position responsible for establishing and implementing new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to lead applications systems analysis and programming activities. Responsibilities: Partner with multiple management teams to ensure appropriate integration of functions to meet goals as well as identify and define necessary system enhancements to deploy new products and process improvements Architect, design, and lead the development of scalable, fault-tolerant Big Data platform using Apache Spark, Hive, and the Apache Iceberg table format. Write and review high-quality, production-grade code in Python or Java for data ingestion, transformation, and orchestration frameworks. Author, optimize, and debug complex SQL queries for large-scale analytical workloads, ensuring high performance and data correctness across distributed systems. Define and enforce best practices for data modeling and table management within the data platform, specifically leveraging Iceberg for schema evolution, partitioning, and data lifecycle policies. Manage and configure job scheduling and dependency management using AutoSys, ensuring reliability, monitoring, and alerting are in place for all production data workflows. Champion and implement robust CI/CD pipelines for data engineering projects using GitHub, including automated testing, deployment strategies, and code quality gates. Serve as the primary technical point of contact for large projects, effectively communicating technical designs, risks, and project status to both engineering teams and senior business stakeholders. Mentor and guide junior and mid-level engineers, fostering a culture of technical excellence, innovation, and continuous improvement through code reviews and knowledge sharing. Proactively identify and resolve performance bottlenecks, data quality issues, and technical debt within the data platform. Collaborate with data architects, product managers, and platform engineers to define the technical roadmap and long-term strategy for the data ecosystem. This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

Requirements

• 10+ years of hands-on experience designing, building, and maintaining large-scale data processing systems using Big Data technologies, including deep expertise in Apache Spark and Hive.
• Excellent, demonstrable hands-on programming experience in Python or Java within a data engineering context.
• Proven ability to write, optimize, and troubleshoot highly complex SQL queries on large datasets.
• Hands-on experience and a strong understanding of the Apache Iceberg table format, including its use cases for schema evolution, time travel, and partitioning.
• Very good knowledge of enterprise-level development and deployment workflows, including job scheduling with AutoSys, version control with GitHub, and implementing CI/CD pipelines.
• Demonstrated experience working on large-scale projects and successfully navigating environments with multiple stakeholders from both technical and business backgrounds.

Responsibilities

• Partner with multiple management teams to ensure appropriate integration of functions to meet goals as well as identify and define necessary system enhancements to deploy new products and process improvements
• Architect, design, and lead the development of scalable, fault-tolerant Big Data platform using Apache Spark, Hive, and the Apache Iceberg table format.
• Write and review high-quality, production-grade code in Python or Java for data ingestion, transformation, and orchestration frameworks.
• Author, optimize, and debug complex SQL queries for large-scale analytical workloads, ensuring high performance and data correctness across distributed systems.
• Define and enforce best practices for data modeling and table management within the data platform, specifically leveraging Iceberg for schema evolution, partitioning, and data lifecycle policies.
• Manage and configure job scheduling and dependency management using AutoSys, ensuring reliability, monitoring, and alerting are in place for all production data workflows.
• Champion and implement robust CI/CD pipelines for data engineering projects using GitHub, including automated testing, deployment strategies, and code quality gates.
• Serve as the primary technical point of contact for large projects, effectively communicating technical designs, risks, and project status to both engineering teams and senior business stakeholders.
• Mentor and guide junior and mid-level engineers, fostering a culture of technical excellence, innovation, and continuous improvement through code reviews and knowledge sharing.
• Proactively identify and resolve performance bottlenecks, data quality issues, and technical debt within the data platform.
• Collaborate with data architects, product managers, and platform engineers to define the technical roadmap and long-term strategy for the data ecosystem.

Benefits

• In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards.
• Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs.
• Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays.
• For additional information regarding Citi employee benefits, please visit citibenefits.com.
• Available offerings may vary by jurisdiction, job level, and date of hire.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees