Java Developer Or Python Developer - Data Lineage & Metadata

Client: CITI – Java Developer or Python Developer (Data Lineage & Metadata)
We are looking for a highly skilled
Java Developer or Python Developer specializing in Data Lineage and Metadata Management
with strong expertise in software engineering, backend development, code parsing, data flow analysis, and modern Gen AI/LLM technologies. The ideal candidate should have hands‑on experience building scalable systems that parse and analyze large, multi‑language codebases to automatically generate accurate data lineage. The successful candidate will be responsible for designing and developing backend services, implementing AI‑powered retrieval capabilities, building deployment pipelines, and delivering clean, efficient, reliable, and maintainable solutions.
Role Snapshot
Job Title: Java Developer or Python Developer – Data Lineage & Metadata
Client: CITI
Work Location: Mississauga, Ontario, Canada
Work Arrangement: Onsite
Technical RequirementsThe candidate should have strong development experience in Java/J2EE or Python, with the ability to design, develop, and implement scalable software solutions.
Java/J2EE Technical Expertise
Strong knowledge of Java/J2EE development.
Experience with Spring Boot, Hibernate, and Object-Relational Mapping (ORM).
Core development expertise, including the ability to write reusable libraries and executable solutions.
Experience working with event-based frameworks.
Knowledge of different software design patterns.
Experience with Oracle Database.
Experience configuring and working with APIs, Graph APIs, and Graph Databases.
Role SummaryThe developer will focus on data lineage and build systems that parse and analyze large, multi‑language codebases to automatically generate accurate data lineage.
What You’ll Do
Design and build engines that parse multiple programming and query languages to extract accurate, column‑level data lineage.
Build Gen AI/LLM‑powered retrieval and assistant capabilities on top of lineage and metadata.
Develop backend services and the interfaces that expose them, from data processing through to user‑facing views.
Own the delivery pipeline, including build, testing, deployment, and production support across environments.
Design Principles We Value
Simplicity First: Favor the simplest design that solves the problem;
avoid unnecessary complexity and premature abstraction.
Separation of Concerns: Establish clear module boundaries, single‑responsibility components, and well‑defined interfaces so individual components can evolve independently.
Correctness and Determinism: Prefer predictable, testable behaviour;
ground AI outputs in verifiable data rather than guesswork.
Performance‑Aware Design: Consider time and space complexity, memory footprint, and efficient data structures and algorithms from the beginning.
Scalability and Extensibility: Design systems so new languages, sources, and capabilities can be added without requiring rewrites.
Robustness: Implement graceful error handling, fault isolation, and defensive design so one bad input cannot bring down the system.
Readability and Maintainability: Develop code and designs that other engineers can easily understand, extend, and debug.
Reuse Over Duplication: Use shared models and common abstractions instead of duplicating logic.
Required Skills
Strong Python development experience with solid object‑oriented and functional design skills.
Strong software engineering fundamentals, including data structures, algorithms, and complexity analysis.
Experience in data lineage and data flow analysis, including parsing and analyzing source code using AST‑based and pattern‑based static analysis techniques, with the ability to read and understand multiple programming languages.
Hands‑on Gen AI/LLM experience, including prompt design, tool/function calling, and agent orchestration.
Understanding of Retrieval‑Augmented Generation (RAG) and vector/semantic search concepts.
Experience designing APIs and backend services, along with front‑end fundamentals to build usable interfaces.
Pipeline and deployment experience, including build/test automation, Continuous Integration/Continuous Delivery (CI/CD), and releasing solutions across environments.
Strong data manipulation and transformation skills.
Nice to Have
Knowledge of graph algorithms and traversal techniques for dependency and lineage tracing.
Understanding of data governance, metadata management, and data cataloguing concepts.
Experience designing systems for long‑running or asynchronous workloads.
Knowledge of infrastructure automation and deployment tooling.
Key Responsibilities
Translate ambiguous requirements into clean, efficient, and well‑structured designs.
Extend parsing and analysis capabilities to new programming languages and frameworks without compromising the overall architecture.
Design and productionize Gen AI/LLM and retrieval features that are accurate and grounded in real data.
Build and maintain deployment pipelines and support delivery across different environments.
Write tests and maintain quality throughout the development lifecycle.
Collaborate on design reviews and continuously raise the engineering standards of the team.
Interview ProcessSelection Process Will Consist Of 3 Interview Levels
L1 – Altimetrik Internal Panel: Interview through Microsoft Teams or Zoom.
L2 – Karat Interview.
L3 – Discussion with the Project Team: Interview through Microsoft Teams or Zoom.
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