Senior Data Developer, Assistant Vice President

Citi • Irving, TX

1d • $107,120 - $160,680

About The Position

Citi is seeking a hands-on Senior Data Developer/Lead to join a small, co-located, high-performing squad. The role develops, implements, and optimizes robust, scalable, and real-time data solutions within the Hadoop ecosystem and streaming platforms. The successful candidate brings deep big data expertise, including Kafka-based streaming, and a record of end-to-end delivery in the banking domain.

The position emphasizes an AI-first approach, using modern AI coding tools to improve efficiency and innovation. It contributes to data ingestion, advanced analytics, reporting, and AI/ML integration while collaborating within an agile team. The developer is expected to ensure data infrastructure performance, security, and governance, take substantial ownership of delivery, and mentor other team members.

The position is in Technology, within Applications Development, and is full-time. The primary location is Irving, Texas. The listed salary range is $107,120 to $160,680. Citi may also offer eligible employees incentive and retention awards, competitive insurance and retirement benefits, wellness programs, and paid time off.

Requirements

• At least 5 years of experience developing, implementing, and optimizing complex Hadoop-based and real-time data platforms, with senior-level hands-on contributions.
• Hands-on experience in AI/ML and modern AI coding tools.
• Strong understanding of Hadoop ecosystem components, including HDFS, YARN, MapReduce, Hive, FastAPI, and Spark.
• Extensive hands-on experience with real-time data streaming technologies, particularly Apache Kafka, including performance optimization.
• Proficiency with Python, PySpark, FastAPI, Unix, SQL, and Delta SQL.
• Experience building and optimizing end-to-end data pipelines using Delta Live Tables (DLT) and Databricks workflows.
• Strong understanding of the Delta Lake storage layer.
• Familiarity with major cloud platforms such as AWS, Azure, and Google Cloud.
• Experience with advanced data modeling principles and practices, including dimensional modeling.
• Proficiency developing and implementing complex ETL/ELT processes for batch and real-time data.
• In-depth knowledge of data warehousing concepts and best practices.
• Understanding and practical experience with AI/ML lifecycle management, MLOps practices, and integration of machine learning models into data solutions, with an AI-first mindset.
• Proven end-to-end project delivery experience for complex data initiatives.
• Strong banking or financial services domain knowledge, including the ability to explain the functional impact of technical work and comply with relevant data standards and regulations.
• Excellent problem-solving skills and ability to work autonomously in a small, high-performing team.
• Strong written and verbal communication skills, including the ability to explain complex technical concepts, mentor others, and contribute to team growth.
• Bachelor’s degree, university degree, or equivalent experience.

Nice To Haves

• Practical exposure to building machine learning models.
• Experience with AI coding tools such as Devin and Copilot.
• Experience with Generative AI concepts and tools and applying them in practical use cases.
• Master’s degree preferred.

Responsibilities

• Develop and implement scalable, efficient data solutions within the Hadoop ecosystem, aligned with enterprise data strategy and best practices.
• Develop, implement, and manage complex Hadoop-based data pipelines and real-time streaming solutions with end-to-end ownership.
• Implement and improve real-time streaming solutions using technologies such as Apache Kafka.
• Translate data requirements from engineers and scientists into technical specifications and practical implementations within a small agile squad.
• Optimize Hadoop clusters and streaming applications for performance, scalability, resource utilization, high throughput, and low latency.
• Maintain and monitor Hadoop and streaming infrastructure to ensure availability, reliability, and data integrity, and resolve issues proactively.
• Implement data security and governance policies in accordance with banking-sector regulatory and compliance requirements.
• Track developments in big data, real-time analytics, AI/ML, and AI coding tools, and recommend or integrate innovative solutions.
• Troubleshoot complex Hadoop and streaming platform issues and mentor less experienced team members.
• Develop Spark-based solutions for near-real-time ingestion, advanced analytics, and reporting.
• Contribute to AI/ML model implementation in data pipelines, including data preparation, feature engineering, and production deployment, and mentor others on best practices.
• Participate in MLOps initiatives covering continuous integration, continuous delivery, and continuous training.
• Own end-to-end delivery of data initiatives from conceptualization through implementation, testing, and deployment.

Benefits

• Medical coverage
• Dental coverage
• Vision coverage
• 401(k)
• Life, accident, and disability insurance
• Wellness programs
• Paid time off, including planned vacation time, unplanned sick leave, and paid holidays
• Eligible employees may receive discretionary and formulaic incentive and retention awards

What This Job Offers

• Job Type: Full-time
• Career Level: Senior