Lead Data Engineer

Role Value Proposition

This team is at the core of Actuarial IT’s Legacy Modernization valuation process and reporting transformation initiatives, leading the design and implementation of modern, AI-enabled architectures. Its mission is to power advanced analytics, business intelligence, and agentic solutions through scalable, secure, and high-performance platforms. By promoting best practices in data governance, performance optimization, and AI-driven data engineering, the team delivers real-time insights and predictive analytics that create tangible business value.

Join Met Life as a Lead Data Engineer and help shape the future of data modernization. In this role, you’ll design and implement AI-driven data architectures that power advanced analytics, business intelligence, and predictive insights. Collaborate with global teams to build scalable, secure, and high-performance platforms that transform legacy systems into cutting-edge solutions driving real business value. The Lead Full Stack Software Engineer is responsible for building, optimizing, and maintaining ETL/ELT pipelines for large, complex datasets, ensuring compliance with data standards and best practices.

Institutionalize best practices and accelerate solution delivery through reusable frameworks, prototypes, and innovation initiatives. To modernize legacy systems and build scalable, AI-enabled data intelligence actuarial valuation platforms that support Met Life’s digital transformation strategy, this role advances the company’s purpose by delivering actuarial solutions using AI‑driven data engineering that enable smarter decisions, better customer experiences, and a more confident future.

• Lead the design and implementation of modern, AI‑enabled data engineering solutions that power advanced analytics and business intelligence.
• Create scalable, secure, and high‑performance data solutions that enable real‑time insights and predictive analytics.
• Oversee data governance, quality, and compliance across enterprise platforms to ensure integrity and trust.
• Manage end‑to‑end data engineering processes, including performance optimization and cloud migration strategies.
• Develop innovative data pipelines and frameworks that support actuarial modeling, reporting, and advanced analytics.
• Coordinate with actuaries, data scientists, business analysts, and technology teams to deliver integrated, impactful solutions.

• Bachelor’s or Master’s degree in Computer Science, or a related field (or equivalent experience).
• 8+ years of experience in data engineering and architecture for enterprise‑scale platforms.
• Expertise in cloud platforms (Azure Databricks) to design and deploy scalable data architectures and solutions.
• Strong expertise in data technologies such as Apache Spark, along with proficiency in data pipeline tools for building robust ETL processes, and hands‑on experience with Databricks features, including Unity Catalog and/or AI/BI Genie.
• Strong knowledge of SQL, Python, and modern data modeling techniques to optimize performance and enable advanced analytics.
• Collaborative mindset with the ability to work across actuarial, analytics, and technology teams in a fast‑paced environment.
• Strategic thinker with a passion for innovation and problem‑solving in complex data ecosystems.

• Practical experience with leading AI/ML frameworks—including Azure ML, Databricks ML, PyTorch, and MLflow—for developing advanced analytics solutions and predictive models.
• Ability to drive innovation and mentor teams, fostering best practices in data engineering, governance, and performance optimization.
• Strong actuarial business acumen with the ability to translate complex technical solutions into measurable business outcomes.

Location Expectation:
This is a hybrid role requiring a minimum of 3 days per week in office.

The expected salary range for this position is $110,000 – $145,000. This role may also be eligible for annual short‑term incentive compensation. All incentives and benefits are subject to the applicable plan terms.