Corporate Vice President, Sr Data Engineer

Location: Lebanon
Posted on: June 23, 2025

Job Description:

Our New York Life culture has laid the foundation for over 175 years of commitment to our employees, agents, policy owners, and the communities where we live and work. Here you become a valued part of a welcoming, inclusive, and caring organization with a long-standing legacy in stability and growth. The strength revolves around our diversified, multi-dimensional business portfolio that goes beyond life insurance. As a Fortune 100 company and industry leader, we provide an environment where you can explore your career ambitions, offering opportunities to tackle meaningful challenges and stretch your skills while balancing work and life priorities. You will be part of an inclusive team guided by our belief to always be there for each other–providing the support and flexibility to grow and reach new heights while making an impact in the lives of others. You are our future, and we commit to investing in you accordingly. Visit our LinkedIn to see how our employees and agents are leading the industry and impacting communities. Visit our Newsroom to learn more about how our company is constantly evolving to meet our clients and employees’ needs. As part of AI&D, youll have the opportunity to contribute to groundbreaking initiatives that shape New York Lifes digital landscape. Leverage cutting-edge technologies like Generative AI to increase productivity, streamline processes, and create seamless experiences for clients, agents, and employees. Your expertise fuels innovation, agility, and growth — driving the companys success . Build, expand, and optimize data pipeline architecture using Amazon Web Services cloud, Python and Pyspark. Utilize tools like Amazon Relational Database Service (AWS DMS), AWS Database Migration Service (AWS DMS), AWS Glue, Amazon Simple Storage Service (AWS S3), AWS Lambda triggers & functions, etc. Leverage Data Engineering strategies, Data Lake/Lakehouse/Data Warehouse technologies, and streaming/real-time data. Use SQL for data analysis. Proficient in other cloud technologies like databricks etc. What you’ll do: • Design and develop enterprise infrastructure and platforms required for data engineering. • Use AWS Cloud technologies to support data needs for expansion of Machine Learning/Data Science capabilities, applications/mobile apps/systems, BI/analytics, and cross-functional teams. • Create methods and routines to transition data from on-premise systems to the AWS Cloud. • Store data in AWS Cloud platform and develop transformational logic based on business rules. • Create and maintain optimal data pipeline architecture. Test and implement data environments. • Assemble large, complex data sets to meet functional/non-functional business requirements. • Build the infrastructure required for optimal ETL/ELT (extraction, transformation, and loading) of data from a wide variety of data sources using SQL and AWS big data technologies. • Utilize AWS Cloud tools like Amazon Relational Database Service (AWS DMS), AWS Database Migration Service (AWS DMS, AWS Glue, Amazon Simple Storage Service (AWS S3), AWS Lambda triggers & functions, etc. • In-depth knowledge of databricks. • Should be able to develop the High level and low level data architecture. • Develop and debug code in PySpark/Spark/Python. Use SQL and/or Postgres. • Use Data Pipeline, workflow management, and orchestration service tools. • Proficient with SQL for data analysis. • Collaborate with Cloud Data Architects, Data Engineers, DBAs, Analytics & Software Engineers. • Interact with stakeholders, Product Management, and Design teams to understand requirements and resolve issues. What you’ll bring: • 8 years as a Cloud Data Engineer, Data Engineer, Data Architect, AWS Engineer, etc. • 3 years with Amazon Relational Database Service (RDS), AWS Database Migration Service (AWS DMS), Amazon Simple Storage Service (S3) Data Lake, AWS Lambda, etc. in shared service, hybrid environments. • Highly scalable Data stores, Data Lake, Data Warehouse, Lakehouse, and unstructured datasets. • Strong expertise in databricks (spark on databricks) delta lake architecture. • Proficient in Python, Scala, or SQL for building data pipelines and processing data. • Data integration, data processing, data streaming, message queuing, and/or ETL/ELT. • Deep knowledge of cloud platforms (Azure, AWS, or GCP) and experience in managing cloud-based data storage and compute resources. • Experience with GIT. • Ability to lead a team of developers. • Bachelor’s degree in Data Science, Computer Engineering, or related field preferred.

Keywords: , Hamilton , Corporate Vice President, Sr Data Engineer, IT / Software / Systems , Lebanon, New Jersey