Applications Development Sr Programmer Analyst - C12 - MISSISSAUGA

Posted 12 Days Ago
Be an Early Applicant
Mississauga, ON, CAN
In-Office
94K-142K Annually
Senior level
Fintech • Financial Services
The Role
Design, build, and maintain scalable data pipelines and enterprise AI agents using Python, FastAPI, PySpark, Kafka, and Databricks. Deploy GenAI agents with Google ADK/Flash LLMs, build data federation and Data Mesh layers (Starburst), automate microservice integrations on cloud-native platforms (OpenShift/Kubernetes) with CI/CD, and integrate agentic tools (Devin.AI, GitHub Copilot, MCP) via prompt engineering. Ensure data quality, security, and regulatory compliance while improving data engineering processes.
Summary Generated by Built In

Job Summary
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 is an intermediate-level position responsible for designing, building, and maintaining robust, scalable data pipelines and solutions that leverage cutting-edge Mandatory platform for the secure and scalable deployment of AI agents, Big Data, Databrick and AI technologies. The ideal candidate is a high-impact individual with a passion for data, analytics, and problem-solving. You will play a key role in driving business engagement and growth by building the next generation of data and analytics platforms.

Responsibilities
  • Design, develop, and maintain scalable, enterprise-grade   AI agents , supporting ELT/ETL processes to handle large data volumes using the Python, FAST API, Microservices , PySpark, Kafka  and Databricks ecosystem.

  • Build and Deploy GEN AI Agents using Googles ADK and Google Flash 2.5+ LLMs to support application automation supports and its deep insights, workflow support with HIL - Human in loop architecture.

  • Build and maintain data federation layers for lambda and Data Mesh architectures using tools like Starburst, with a strategy for adopting AI-based use cases (e.g., machine learning, deep learning, 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 openshift or Kubernates architecture including CI/CD pipelines.

  • Integrate and leverage agentic AI tools (e.g., Devin.AI, Github 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 the 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 Citi, its clients, and assets by driving compliance with applicable laws, rules, and regulations. Adhere to Policy, apply sound ethical judgment, and escalate, manage, and report control issues with transparency.


Qualifications
Required:
  • 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, FAST API or Spring boot, Google ADK, LLM itegrations, including Devin.AI or Github 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.

Preferred:
  • 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).

Education
  • Bachelor’s degree in Computer Science, Engineering, or a related field.

  • Master’s degree is a plus.

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Job Family Group: Technology

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Job Family:Applications Development

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Time Type:Full time

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Primary Location Full Time Salary Range:$94,300.00 - $141,500.00

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Most Relevant Skills Please see the requirements listed above.

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Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.

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Automated Processing and AI

We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.

Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.

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This job opening is for an existing job vacancy.

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Citi 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.

 

If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.
View Citi’s EEO Policy Statement and the Know Your Rights poster.

Skills Required

  • 8+ years of overall large-scale application development experience with recent mandatory platform for secure deployment of AI agents
  • Minimum 5+ years in a Python and PySpark engineering lead role building enterprise-grade, high-volume ELT/ETL processes using PySpark and Databricks
  • Hands-on experience with agentic AI development using YAML, JSON, FastAPI or Spring Boot, Google ADK, and LLM integrations
  • Experience integrating agentic tools such as Devin.AI or GitHub Copilot and integrating models via platforms like MCP using prompt engineering
  • Proven experience developing and automating microservice integrations to support data-intensive applications
  • Proficiency in at least one data analytics language such as Python or Scala
  • Strong SQL skills and experience with relational databases
  • Deep understanding of data modeling, data warehousing concepts, Data Mesh architecture, and data federation
  • Experience with cloud-native infrastructure and OpenShift or Kubernetes architectures, including CI/CD pipelines
  • Excellent communication, collaboration, and problem-solving skills
  • Bachelor's degree in Computer Science, Engineering, or related field
  • Experience with frontend technologies such as Angular or React JS for building data-driven interfaces
  • Experience with cloud-based big data platforms (Cloudera, Databricks, AWS, Azure, GCP)
  • Practical experience applying AI/ML techniques to business problems
  • Familiarity with containerization technologies (Docker, Kubernetes)
  • Experience in data engineering within banking retail product domains (Cards, Mortgage, Deposits, Wealth Management)
  • Relevant industry certifications (e.g., AWS Certified Big Data - Specialty, Azure Data Engineer Associate)

Citi Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Citi and has not been reviewed or approved by Citi.

  • Healthcare Strength Benefits coverage is positioned as comprehensive, including health, dental, and vision insurance plus on-site clinics, prescription drug support, and disability coverage. Family-building support such as fertility assistance is described as a notable differentiator within the overall package.
  • Retirement Support Retirement benefits are framed as strong, highlighted by a 401(k) with matching and additional plan options like a Roth 401(k). Financial support is reinforced through discounts and broader financial guidance resources tied to the benefits ecosystem.
  • Wellbeing & Lifestyle Benefits Wellbeing support extends beyond insurance through programs like an Employee Assistance Program, counseling/legal resources, and gym or wellness reimbursement. These offerings increase the perceived total rewards value even when cash compensation sentiment varies by role.

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The Company
HQ: Kwun Tong, Kowloon
223,850 Employees

What We Do

Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients. We have 200 years of experience helping our clients meet the world's toughest challenges and embrace its greatest opportunities. We are Citi, the global bank – an institution connecting millions of people across hundreds of countries and cities.

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