Lead Data Engineer

A career at New York Life offers many opportunities. To be part of a growing and successful business. To reach your full potential, whatever your specialty. Above all, to make a difference in the world by helping people achieve financial security. It's a career journey you can be proud of, and you'll find plenty of support along the way. Our development programs range from skill-building to management training, and we value our diverse and inclusive workplace where all voices can be heard. Recognized as one of Fortune's World's Most Admired Companies, New York Life is committed to improving local communities through a culture of employee giving and service, supported by our Foundation. It all adds up to a rewarding career at a company where doing right by our customers is part of who we are, as a mutual company without outside shareholders. We invite you to bring your talents to New York Life, so we can continue to help families and businesses "Be Good At Life." To learn more, please visit LinkedIn, our Newsroom and the Careers page of www.NewYorkLife.com.
Ranked number 61 on the 2016 Fortune 500 list, New York Life Insurance Company (?the Company?) is the oldest and the largest mutual life insurance company in the United States and one of the largest life insurers in the world. Founded in 1845, New York Life is headquartered in New York City and maintains operations in all fifty states as well as Mexico, through a network of more than 17,000 agents and more than 10,000 employees. New York Life is consistently recognized as a great place to work and is often named on the lists of "Best Companies":
Title: Lead Data Engineer
Location: CNJ/JCNJ/HO
Job Level: MG1
The Information Delivery team provides transformative data capabilities and solutions that serve as the core data, reporting, and analytics platform for the Insurance & Agency Group at New York Life (NYL). The Information Delivery team is looking for a Lead Data Engineer with the skills listed below.
Experience working with Polyglot Data Storage technologies in the cloud, Data Lake (HDFS, Blog storage), RDMS (Oracle, SQL, SQL DW, Redshift) and NoSQL solutions (Key Value, Document, Column and Graph). The installation, configuration, administration and governance of these environments on-prem and the cloud.
MS/BS in Computer Science, Information Systems, or related field preferred and/or equivalent experience
Data Ingestion
Experience in data processing operations (ETL / ELT) that is optimized and scalable, encapsulated in workflows, that transform source data, move data between multiple sources, load the processed data into an analytical data store using cloud orchestration technology such as Azure Data Factory or Apache Oozie, Sqoop, AWS Data Pipeline, AWS Glue, Informatica.
Batch Processing
Experience in the Hadoop echo system, reading source files, processing them, and writing the output to new files or data stores using Hive, Pig, or custom Map/Reduce jobs in a Hadoop cluster, or using Java, Scala, or Python programs in an Hadoop Spark cluster.
Stream Processing and Real-Time Message Ingestion
Experience with real-time data sources and message ingestion for processing by filtering, aggregating, and preparing the data for analysis. Technologies such as Spark Streaming and Kafka, AWS Kinesis, Azure IOT or Event Hub etc. Good understanding of Lambda Architecture. Experience building and productionizing micro-services and APIs.
ML and AI
Identify and formulate various challenges in user support domains as Machine Learning (ML) problems.
Design, develop, validate and deploy proposed ML solutions.
Analysis and Reporting and Analytical Data Stores
Knowledge of solutions (complex reports, dashboards, and scorecards) that provide insights into the data through analysis and reporting with Enterprise Data Lake initiatives including Data Model development, Semantic Layer Development is a plus.
Knowledge of solutions for shared data usage using cloud based data store technologies such as AWS (Redshift) or Azure (SQL Data Warehouse), SSAS or NoSQL technology such as HBase, or Hive databases in a distributed data store is a nice to have.
Working knowledge in any one of the ETL tools is a plus.
Knowledge of the reporting tools like PowerBI, Tableau, Qlik Sense, QlikView is a plus.
Other Responsibilities:
Ability to manage a team in an on/offshore model
Ability to interact with multiple technical teams and the data governance team to come with a data governance framework.
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