Applications Development Sr Programmer Analyst - C12

Job Overview

Working at the company 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 the company, you’ll have the opportunity to grow your career, give back to your community and make a real impact.

We are seeking a highly motivated and experienced Principal Engineer to join our Retail and Wealth Risk Engineering team under the Enterprise Risk Technology platform. This intermediate‑level position is responsible for designing, building, and maintaining robust, scalable data pipelines and solutions that leverage cutting‑edge AI and big‑data technologies, including the mandatory platform for secure and scalable deployment of AI agents, Big Data, Databricks, and AI technologies.

The ideal candidate is a high‑impact individual with a passion for data, analytics, and problem‑solving and will play a key role in driving business engagement and growth by building the next generation of data and analytics platforms.

• Design, develop, and maintain scalable enterprise‑grade AI agents supporting ELT/ETL processes to handle large data volumes using Python, FastAPI, microservices, PySpark, Kafka, and the Databricks ecosystem.
• Build and deploy GEN AI agents using Google ADK and Google Flash 2.5+ LLMs to support application automation and gain deep insights, providing workflow support with human‑in‑the‑loop architecture.
• Build and maintain data federation layers for lambda and Data Mesh architectures using tools like Starburst
  , with a strategy to adopt AI‑based use cases such as machine learning, deep learning, and NLP to drive efficiency.
• Develop, deploy, and automate microservice integrations to support data‑intensive applications, ensuring scalability, resilience, and maintainability using cloud‑native infrastructure and Open Shift or Kubernetes architecture, including CI/CD pipelines.
• Integrate and leverage agentic AI tools (e.g., Devin.
  
  AI, Git Hub Copilot) and platforms (e.g., MCP) through advanced prompt engineering to enhance development and operational efficiency.
• Ensure data quality, integrity, and security throughout the entire data lifecycle.
• Contribute to continuous improvement of data engineering processes, standards, and best practices within the team.
• Appropriately assess risk when business decisions are made, demonstrating consideration for the firm’s reputation and safeguarding the company, its clients, and assets by driving compliance with applicable laws, rules, and regulations, applying sound ethical judgment, and escalating, managing, and reporting control issues with transparency.

• 8+ years of overall experience in large‑scale application development with recent mandatory platform for the secure and scalable deployment of AI agents into application contexts.
• Minimum of 5+ years of proven experience in a Python and PySpark engineering lead role focused on building enterprise‑grade, high‑volume ELT/ETL processes using the PySpark and Databricks ecosystem.
• Hands‑on experience with agentic AI development using YAML, JSON, FastAPI or Spring Boot, Google ADK, LLM integrations, including Devin.
  
  AI or Git Hub Copilot, and integrating models via platforms like MCP using advanced prompt engineering.
• Proven experience developing and automating microservice integrations to support data‑intensive applications.
• Proficiency in at least one programming language commonly used for data analytics, engineering, such as Python or Scala.
• Strong SQL skills and experience with various relational databases.
• Deep understanding of data modeling, data warehousing concepts, Data Mesh architecture, and data federation.
• Excellent communication, collaboration, and problem‑solving skills.

• Experience with cloud‑based Big Data platforms (e.g., Cloudera, Databricks, AWS, Azure, GCP).
• Experience with frontend technologies such as Angular or React JS for building data‑driven application interfaces.
• Practical experience applying AI/ML techniques to solve real‑world business problems.
• Familiarity with containerization technologies (e.g., Docker, Kubernetes).
• Experience in data engineering within the banking retail products domain (e.g., Cards, Mortgage, Deposits, Wealth Management).
• Relevant industry certifications (e.g., AWS Certified Big Data - Specialty, Azure Data Engineer Associate).

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• Master’s degree is a plus.

$94,300.00 - $

* the company is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.*