Sr. Data Engineer - Assistant Vice President

Sr. Data Engineer - Assistant Vice President

Working at Citi is far more than just a job. A career with us means joining a team of more than 230,000 dedicated people from around the globe. At Citi, you'll have the opportunity to grow your career, give back to your community and make a real impact.

Job Overview

The Applications Development Senior Programmer Analyst is an intermediate level position responsible for participation in the establishment and implementation of new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to contribute to applications systems analysis and programming activities.

We are seeking a highly motivated and experienced Data Engineer to join our Data Engineering/Consumer Data Platform team. In this role, you will be a key player in designing, building, and maintaining robust and scalable data pipelines and solutions that leverage cutting-edge Big Data technologies, including AI.

The ideal candidate is a high-impact individual with a passion for data and analytics. You are a problem-solver at heart, with a proven ability to collaborate across teams and drive innovative solutions. You are passionate about using data to drive customer engagement and growth. This role demands a deep understanding of data engineering principles, experience with distributed systems, and a passion for applying AI techniques to solve real-world business challenges. You will be responsible for the volume, quality, timeliness, and delivery of end results.

Do you have what it takes to join our team? We are looking for candidates who share our passion for tackling complex data challenges head-on and are driven to build the next generation of data and analytics platforms.

Responsibilities:

• Design, develop, and maintain scalable and efficient data pipelines using Big Data technologies (e.g., Hadoop, Spark, Kafka, Hive, Parquet, Avro) to ingest, process, and transform large volumes of structured and unstructured data.
• Implement and optimize ETL/ELT processes for data ingestion, cleansing, transformation, and loading into data warehouses, data lakes, and other data stores.
• Integrates subject matter and industry expertise within a defined area.
• Applies in-depth understanding of how data engineering and analytics collectively integrate within the sub-function as well as coordinates and contributes to the objectives of the entire function.
• Build and maintain data pipelines outcomes as data federations layers for lambda and Data Mesh architecture using tools like Starburst with strategy for adopting AI techniques-based use cases to drive efficiency and reduce data copies (e.g., machine learning, deep learning, natural language processing) to extract insights, automate processes, and enhance decision-making.
• Develop and deploy microservices-based architectures to support data-intensive applications and ensure scalability, resilience, and maintainability.
• Ensure data quality, integrity, and security throughout the data lifecycle.
• Contribute to the continuous improvement of data engineering processes, standards, and best practices.
• Effectively communicate technical concepts and solutions to both technical and non-technical audiences.
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency, as well as effectively supervise the activity of others and create accountability with those who fail to maintain these standards.
• Conduct tasks related to feasibility studies, time and cost estimates, IT planning, risk technology, applications development, model development, and establish and implement new or revised applications systems and programs to meet specific business needs or user areas
• Monitor and control all phases of development process and analysis, design, construction, testing, and implementation as well as provide user and operational support on applications to business users
• Utilize in-depth specialty knowledge of applications development to analyze complex problems/issues, provide evaluation of business process, system process, and industry standards, and make evaluative judgement
• Recommend and develop security measures in post implementation analysis of business usage to ensure successful system design and functionality
• Consult with users/clients and other technology groups on issues, recommend advanced programming solutions, and install and assist customer exposure systems
• Ensure essential procedures are followed and help define operating standards and processes
• Has the ability to operate with a limited level of direct supervision.
• Can exercise independence of judgement and autonomy.
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.

Qualifications:

• 8+ years overall experience in a Big Data or Enterprise large scale Apps development using scalable tools like Databricks, Scala, Java and python ecosystem.
• Minimum 5+ years of proven experience in a Data Engineering lead role with a strong focus on Big Data, data federation and data extractions data mesh architecture
• Deep understanding of data modeling, data warehousing concepts, methodologies, and best practices.
• Expertise in designing, building, and maintaining data pipelines using Big Data technologies such as Hadoop, Spark, Hive, Kafka, and related ecosystems.
• Proficiency in at least one programming language commonly used for data engineering, such as Python, Java, or Scala.
• Hands-on experience with ETL/ELT tools and Microservices frameworks.
• Practical experience in applying AI/ML techniques to solve real-world problems.
• Familiarity with microservices architecture and containerization technologies (e.g., Docker, Kubernetes).
• Strong SQL skills and experience with relational databases.
• Excellent communication, collaboration, and problem-solving skills.
• Ability to work independently and as part of a team.
• Passion for data and technology with a strong desire to learn and grow.
• Experience in systems analysis and programming of software applications
• Experience in managing and implementing successful projects
• Ability to work under pressure and manage deadlines or unexpected changes in expectations or requirements

Education:

• Bachelor's degree in computer science & engineering, or a related field.
• Master's degree is a plus.

Preferred Qualifications:

• Experience with cloud-based Big Data platforms (e.g., Cloudera, Databricks, AWS, Azure, GCP).
• Experience in working on data engineering on Bank Retail products – Cards, Mortgage, Deposits and wealth domain exposure
• Certifications in relevant technologies (e.g., AWS Certified Big Data - Specialty, Azure Data Engineer Associate).
• Contributions to open-source projects or participation in data engineering communities.