MetLife

Role Value Proposition  

The MetLife Finance and Risk Management (FRM) organization is evolving to enable MetLife’s New Frontier strategy. With a strong vision in place, we are a global function focused on driving digital technology strategies for key corporate functions within MetLife including, Finance, Actuarial, Reinsurance, Legal, Human Resources, Employee Experience, Risk, Treasury, Audit and Compliance. In partnership with our business leaders, we develop and deliver seamless technology experiences to our employees across the entire employee lifecycle. Our vision and mission is to create innovative, transformative and contemporary technology solutions to empower our leaders and employees so they can focus on what matters most, our customers. We are technologists with strong business acumen focused on developing our talent to continually transform and innovate.

As part of Tech Talent Transformation (T3) agenda, MetLife is establishing a Technology Center in India. This technology center will perform as an integrated organization between onshore, offshore, and strategic vendor partners in an Agile delivery model.

The Director, Product Development Engineering will be part of the larger Finance and Risk Management (FRM) leadership team. As a key technical and people leader, you will lead teams that design and oversee implementation and maintenance of scalable applications, implement efficient data solutions, and drive data-driven strategies for our organization. Your expertise in Azure, Databricks, and big data technologies will be critical in optimizing data flows and empowering analytics initiatives. You will closely collaborate with multiple stakeholders and teams to deliver data-driven insights and solutions, supporting risk modeling, pricing strategies, and other key business initiatives.

Key Relationships 

Internal Stake Holder – FRM Leadership team, India FRM Technology AVP, Business process Owners for US Actuarial

Key Responsibilities 

·        People Management - Managing software engineers located across multiple locations, upskilling/reskilling, hiring / retention agenda and adoption of engineering culture.

·        Stakeholder Management - Managing key business stakeholders to deliver the required technology capabilities to support the digital transformation agenda. Driving prioritization of the product backlog. This includes managing key vendors providing the resources, SaaS & other capabilities. 

·        Stay up to date with emerging technologies and drive innovation.

·        Ways of Working – Adoption of the Agile ways of working in the software delivery lifecycle. 

·        E2E Software Lifecycle Management (Architecture, Design, Development, Testing & Production)  

·        Driving the decisions and implementation of technology best practices, architecture and technology stack including adoption of cloud, AI/Data, and other relevant emerging technology that is fit-for-purpose.  

·        Lead the design, development, and maintenance of scalable data architectures and pipelines in Azure Cloud environments.

·        Ensure the integrity, security, and quality of data through robust data governance practices.

·        Implement performance tuning strategies to optimize big data processing workflows.

·        Guide and support peer reviews of solution designs and related code, ensuring adherence to best practice guidelines and compliance with security and privacy mandates.  

·        Ensure disaster recovery, privacy, and security are aligned to enable application/platform stability, including technology currency management.  

·        Partner with Cyber & IT Security, Data Analytics, Infrastructure, Global Risk Management, Compliance, and Internal Audit to provide the holistic provision of technology services including risks, controls and security, to the business 

Education 

·        A Bachelors/master's degree in computer science or equivalent field.

Experience 

·        13+ years' experience leading software engineering teams

·        Proven experience (5+ years) in data engineering, big data processing, and distributed systems.

·        Proficiency in Azure services (Data Factory, Azure Synapse, Azure Data Lake, Event Hubs).

·        Strong hands-on experience with Databricks and Spark for big data processing.

·        Expertise in PySpark programming for data processing workflows.

·        Deep understanding of ETL/ELT processes, data modeling, and data warehousing principles.

·        Familiarity with cloud-native architectures and CI/CD pipelines.

·        Experience with data governance, security, and compliance practices.

·        Excellent problem-solving and communication skills.

·        Strong leadership and mentoring abilities.

·        Proficiency in software development lifecycle including CI/CD, test driven development, domain driven design and Agile ways of working. 

·        Proven track record in partnering with the business to deliver mission critical transformation via Agile approach.

Preferred Skills:

·        Knowledge of additional programming languages like Python and SQL.

·        Familiarity with actuarial tools such as Prophet or other risk modeling systems.

·        Experience with DevOps tools and practices (Azure DevOps, Terraform).

·        Understanding of machine learning workflows and MLOps practices.

·        Proficiency in data visualization tools (Power BI). 

Soft Skills:

·        Strong leadership and project management capabilities.

·        Excellent problem-solving, communication, and stakeholder management skills.

·        Ability to balance technical innovation with business value delivery.

Skills and Competencies: 

Competencies  

·        Communication: Ability to influence and help communicate the organization’s direction and ensure results are achieved 

·        Collaboration: Proven track record of building collaborative partnerships and ability to operate effectively in a global environment 

·        People Management: Inspiring, motivating and leading diverse and distributed teams 

·        Diverse environment: Can-do attitude and ability to work in a high paced environment 

Technical Stack:

·        Programming: Python, PySpark, Scala, and SQL for data transformation and analytics workflows.

·        Azure Services: Azure Data Factory, Azure Synapse Analytics, Azure Data Lake, Azure Storage, and Event Hubs.

·        Databricks Platform: Strong knowledge of cluster management, performance tuning, job scheduling, and advanced analytics with Spark.

·        Big Data Tools: Apache Spark, Delta Lake, and distributed computing concepts.

·        Data Security: Security best practices including RBAC, encryption, and GDPR compliance strategies.

·        CI/CD: DevSecOps for DataOps using GitHub Actions, Azure DevOps, or similar tools for automation.

·        Data Governance: Knowledge of data quality frameworks, lineage tracking, and metadata management.

·        Cloud Infrastructure: Azure networking, IAM, and infrastructure monitoring.

Certifications

Azure Data Engineer / Azure AI Engineer

Azure Architect

Data Bricks – Azure platform Architect