MetLife

The Team You Will Join

MetLife is on a transformational journey into the New Frontier.  Working closely with our business partners, we are embarking on a transformation that will drive a holistic and cohesive product-aligned model, enabled by an end-to-end delivery capability to drive our highest impact enterprise strategic agenda.  Within MetLife Global Technology – Corporate Systems - Controls, our team assists our IT and business partners in solving complex operational and risk management challenges by rapidly delivering lasting transformations with speed and discipline. Driven by passion and purpose, you will be instrumental in driving change and implementing MetLife’s product model for our businesses while aligning our brand and technology to bring immediate value to our customers and partners.

The Opportunity

MetLife Finance & Risk Management Technology – Controls IT is seeking a Senior Data Engineering & AI/ML Engineer to play a critical role in building and modernizing data and analytics solutions that support Risk, Compliance, and Internal Audit functions.

The ideal candidate brings strong hands‑on engineering expertise, coupled with the ability to collaborate, communicate, and lead across product, engineering, and business teams. This role requires deep experience in data engineering, system integration, and AI/ML enablement, along with a solid understanding of engineering best practices and developer enablement.

This position is both hands‑on and strategic, with responsibilities that include guiding teams through data modeling, architecture and design decisions, platform modernization, and agile delivery practices.

How You’ll Help Us Build a Confident Future (Key Responsibilities)

• Partner closely with product owners and stakeholders to plan, prioritize, and deliver high‑impact business outcomes aligned with enterprise risk and control objectives.
• Lead the design, development, testing, and deployment of scalable data engineering and data processing pipelines.
• Define and maintain architecture, design, and technical documentation to support long‑term platform sustainability.
• Oversee operational support for complex data systems and workflows, including root cause analysis and issue resolution.
• Champion and promote engineering best practices across Data Engineering, Data Platforms, AI/ML, and Cloud technologies.
• Provide technical leadership and guidance to teams on data modeling, integration patterns, performance optimization, and modernization initiatives.
• Support agile delivery by translating business needs into clear technical requirements, user stories, and prioritized backlogs. 

Required Skills

• Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or a related field.
• Strong proficiency in Python and SQL, with deep experience in database design, query optimization, and performance tuning across large‑scale data systems.
• 5+ years of hands‑on experience building and optimizing data engineering pipelines, leveraging ETL platforms (e.g., Informatica, Pentaho), and/or Modern data platforms (e.g., Databricks, Snowflake, Hadoop).
• 5+ years of practical experience with AI/ML technologies and libraries, such as PySpark, Pandas, NumPy, LangChain, Hugging Face, and LLM/RAG integration and prompt engineering.
• 3+ experience working with GenAI / Large Language Models (LLMs) such as OpenAI and Copilot, and integration via API.
• Experience in data modeling (dimensional, canonical, or domain‑oriented models) and designing analytics‑ready datasets and semantic layers.
• Hands‑on experience with Agile delivery frameworks and DevOps tooling (e.g., Azure DevOps, GitHub, Jira).
• Excellent verbal and written communication skills, with the ability to build strong partnerships across technical and business stakeholders. 

Preferred Skills

• Hands‑on experience in custom software development within a cloud‑based DevOps environment, including familiarity with CI/CD automation.
• Experience implementing data quality checks, validation frameworks, lineage, and governance controls in regulated environments.
• Hands‑on experience designing and operating data solutions on cloud platforms (preferably Azure), including storage, compute, and networking fundamentals.
• Familiarity with Enterprise Risk Management, Compliance, Internal Audit, or other GRC domains.
• Experience within Financial Services or a global insurance organization.