Corporate Planning & Management, Data Engineering, New York, Associate

About the role

As a Data Engineer on our team, you will design, develop, and maintain software and data solutions across the entire software lifecycle. You will build responsive, intuitive experiences and robust services that power financial planning, expense management, and risk platforms. You will leverage AI tools and techniques to accelerate development, improve code quality, and enhance platform capabilities. You will establish robust governance frameworks including logging, explainability, and auditability to ensure AI quality and reliability. You will collaborate globally with sponsors, users, and engineering colleagues across multiple divisions to create end-to-end solutions that meet complex business requirements. You will participate in code reviews to ensure quality, maintainability, and adherence to engineering best practices. You will take technical ownership of features and components, managing multiple stakeholders and driving delivery within a global team. You will stay current with the latest advancements in AI/ML platforms, tools, and software engineering practices to continuously improve our solutions.

Responsibilities

• Design, develop, and maintain software and data solutions across the entire software lifecycle from requirements gathering and architecture through implementation, testing and deployment.
• Build responsive, intuitive experiences and robust services that power financial planning, expense management, and risk platforms.
• Leverage AI tools and techniques (e.g., code-generation assistants, LLM-powered automation, prompt engineering, Spec-Driven Development) to accelerate development, improve code quality, and enhance platform capabilities.
• Build and maintain knowledge graph and RAG systems to enable document and data retrieval, querying and searching.
• Establish robust governance frameworks including logging, explainability, and auditability to ensure AI quality and reliability.
• Collaborate globally with sponsors, users, and engineering colleagues across multiple divisions to create end-to-end solutions that meet complex business requirements.
• Participate in code reviews to ensure quality, maintainability, and adherence to engineering best practices.
• Take technical ownership of features and components, managing multiple stakeholders and driving delivery within a global team.
• Stay current with the latest advancements in AI/ML platforms, tools, and software engineering practices to continuously improve our solutions.

Requirements

• Bachelor's or master's degree in Computer Science, Computer Engineering, Data Engineering or a similar field of study.
• 3+ years of proficiency in using programming languages (Java, Python etc) to solve data science problems.
• Data Science & Engineering — experience using industry-standard libraries (e.g., Pandas, NumPy, PySpark, TensorFlow/PyTorch) to build scalable data pipelines, perform data modeling, and enable enterprise insights on large, complex datasets.
• Strong analytical and problem-solving skills - experience with algorithms, data structures, and software design.
• Familiarity in utilizing AI tools for software development (e.g., AI-assisted coding, code review tools, LLM-based productivity tools).
• Foundational understanding of AI and agentic systems - familiarity with concepts such as large language models, prompt engineering, retrieval-augmented generation (RAG) etc.
• Comfortable with technical ownership, managing multiple stakeholders, and working as part of a global team.

Qualifications

• Preferred - Experience That Can Set You Apart
• GenAI & Intelligent Data Retrieval using vector databases, embedding models, and agentic frameworks (e.g., LangChain) — to enable intelligent querying and synthesis of insights across large enterprise data assets.
• Experience with Distributed Databases & Search Platforms— building and optimizing scalable, distributed data systems (e.g ElasticSearch, OpenSearch) with a focus on indexing, query performance, and real-time data retrieval; familiarity with search relevance tuning, vectors and embeddings across large datasets.
• Advanced Data Analytics & Data Science experience applying data science methodologies — including statistical analysis, predictive modeling, and knowledge graphs — across diverse data types.
• Familiarity with MLOps practices including CI/CD for ML, model deployment, and monitoring.
• Knowledge of cloud-native solutions (preferably AWS).
• Knowledge of the financial industry - corporate planning, expense management, or risk functions.

Skills

• Programming Languages (Java, Python etc)
• Industry-standard Libraries (Pandas, NumPy, PySpark, TensorFlow/PyTorch)
• AI Tools for Software Development (e.g., AI-assisted coding, code review tools, LLM-based productivity tools)
• Large Language Models, Prompt Engineering, Retrieval-Augmented Generation (RAG)
• Vector Databases, Embedding Models, Agentic Frameworks (LangChain)
• Distributed Databases & Search Platforms (ElasticSearch, OpenSearch)
• MLOps Practices (CI/CD for ML, Model Deployment, Monitoring)
• Cloud-Native Solutions (AWS)
• Financial Industry Knowledge (Corporate Planning, Expense Management, Risk Functions)

Benefits

We offer access to modern cloud-native architectures, modern AI-driven developer productivity tools (Copilot, Claude Code etc), distributed systems, and large-scale data pipelines. We provide a collaborative, global team where you can learn from experts and grow your career. We also offer the opportunity to work on high-impact platforms that directly influence firm-wide financial planning and operational resilience.

Pay

Details on pay are not specified in this job description.

Schedule

Details on schedule are not specified in this job description.