Corporate Vice President, Sr Data Engineer Position Available In Madison, New York

Job Description:

Our New York Life culture has laid the foundation for over 175years of commitment to our employees, agents, policy owners, andthe communities where we live and work. Here you become a valuedpart of a welcoming, inclusive, and caring organization with along-standing legacy in stability and growth. The strength revolvesaround our diversified, multi-dimensional business portfolio thatgoes beyond life insurance. As a Fortune 100 company and industryleader, we provide an environment where you can explore your careerambitions, offering opportunities to tackle meaningful challengesand stretch your skills while balancing work and life priorities.

You will be part of an inclusive team guided by our belief toalways be there for each other-providing the support andflexibility to grow and reach new heights while making an impact inthe lives of others. You are our future, and we commit to investingin you accordingly. Visit our LinkedIn to see how our employees andagents are leading the industry and impacting communities. Visitour Newsroom to learn more about how our company is constantlyevolving to meet our clients and employees’ needs. As part ofAI&D, youll have the opportunity to contribute togroundbreaking initiatives that shape New York Lifes digitallandscape. Leverage cutting-edge technologies like Generative AI toincrease productivity, streamline processes, and create seamlessexperiences for clients, agents, and employees. Your expertisefuels innovation, agility, and growth — driving the companyssuccess . Build, expand, and optimize data pipeline architectureusing Amazon Web Services cloud, Python and Pyspark. Utilize toolslike Amazon Relational Database Service (AWS DMS), AWS DatabaseMigration Service (AWS DMS), AWS Glue, Amazon Simple StorageService (AWS S3), AWS Lambda triggers & functions, etc. LeverageData Engineering strategies, Data Lake/Lakehouse/Data Warehousetechnologies, and streaming/real-time data. Use SQL for dataanalysis. Proficient in other cloud technologies like databricksetc. What you’ll do:

• Design and develop enterprise infrastructureand platforms required for data engineering.
• Use AWS Cloudtechnologies to support data needs for expansion of MachineLearning/Data Science capabilities, applications/mobileapps/systems, BI/analytics, and cross-functional teams.
• Createmethods and routines to transition data from on-premise systems tothe AWS Cloud.
• Store data in AWS Cloud platform and developtransformational logic based on business rules.
• Create andmaintain optimal data pipeline architecture. Test and implementdata environments.
• Assemble large, complex data sets to meetfunctional/non-functional business requirements.
• Build theinfrastructure required for optimal ETL/ELT (extraction,transformation, and loading) of data from a wide variety of datasources using SQL and AWS big data technologies.
• Utilize AWSCloud tools like Amazon Relational Database Service (AWS DMS), AWSDatabase Migration Service (AWS

DMS, AWS

Glue, Amazon SimpleStorage Service (AWS S3), AWS Lambda triggers & functions, etc.

• In-depth knowledge of databricks.
• Should be able to develop theHigh level and low level data architecture.
• Develop and debugcode in PySpark/Spark/Python. Use SQL and/or Postgres.
• Use DataPipeline, workflow management, and orchestration service tools.
• Proficient with SQL for data analysis.
• Collaborate with CloudData Architects, Data Engineers, DBAs, Analytics & SoftwareEngineers.
• Interact with stakeholders, Product Management, andDesign teams to understand requirements and resolve issues. Whatyou’ll bring:
• 8 years as a Cloud Data Engineer, Data Engineer,Data Architect, AWS Engineer, etc.
• 3 years with Amazon RelationalDatabase Service (RDS), AWS Database Migration Service (AWS DMS),Amazon Simple Storage Service (S3) Data Lake, AWS Lambda, etc. inshared service, hybrid environments.
• Highly scalable Data stores,Data Lake, Data Warehouse, Lakehouse, and unstructured datasets.
• Strong expertise in databricks (spark on databricks) delta lakearchitecture.
• Proficient in Python, Scala, or SQL for buildingdata pipelines and processing data.
• Data integration, dataprocessing, data streaming, message queuing, and/or ETL/ELT.
• Deepknowledge of cloud platforms (Azure, AWS, or GCP) and experience inmanaging 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 relatedfield preferred.