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SENIOR ASSOCIATE LEVELPF4 M

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.

Position: Senior ETL DataStage Developer (New York, New York)

Duties: Leverage theoretical knowledge of Computer Science, Computer Information Systems, and Engineering to develop and manage New York Life's corporate Salesforce initiatives. Oversee the implementation of ETL projects through regularly communicating, managing, and setting expectations with both internal stakeholders and Agile teams. Leverage knowledge of IBM DataStage to analyze reporting requirements, determine development methods, Develop ETL jobs, and perform other data warehousing functions. Write complex SQL and PL/SQL queries around Data Analysis, Data Lineage, and Reconciliation in Oracle. Create Data Lineage documents, Source-to-Target (STM) mapping documents and low-level technical specification documents. A critical part of, role involves developing, implementing, and managing database ETL projects using the sophisticated IBM DataStage platform. IBM DataStage is a set of data integration tools used to design develop and run database development and ETL jobs. The platform allows developers to create a framework for developing the jobs that move data from source systems to target systems, as well as deliver to data warehouses, data marts, and other enterprise applications.

Requirements: Master's degree in Computer Science, Computer Engineering or Electrical Engineering (willing to accept foreign education equivalent) plus three years' experience performing database ETL or, alternatively, a Bachelor's degree in Computer Science, Computer Engineering, or Electrical Engineering (willing to accept foreign education equivalent) and five years' experience as noted above. Specific skills/other requirements Must possess one year of the following: Developing ETL jobs using IBM DataStage Designer 11. 5 /9. 1 to extract the data from different complex source systems (Feed Files, Databases), apply transformations (business rules) and load into target systems for business needs and utilizing Big Data technologies (Hadoop, Hive) for huge data extractions. Creating data models, databases, solution designs, and data architecture documentation for complex information systems in Oracle, TOAD, Erwin, and PL/SQL Developer. Writing re-usable complex SQL queries (using joins, subqueries) for analyzing data and identifying data gaps between source and target and preparing Source to Target (STM) mapping documents based on BRD & TSD. Working on OLTP (On-Line Transaction Processing) and OLAP (On-Line Analytical Processing) systems and Normalization forms. Interacting with subject matter experts (SMEs) to understand the characteristics (accuracy, completeness, consistency, uniqueness, and timeliness) of data to determine development methods for dataflow from source to target according to business rules. Interacting with business team and business analyst (Actuarial Business Group, Project Manager) to understand the business requirements (BRDs) and to prepare technical specification documents (TSD). Performing performance techniques to improve the performance for large volume of data including adding/improving Indexes, optimizing queries, rewriting queries (subqueries), avoiding use of non-correlated scalar subqueries, building efficient store procedures/materialized views, and implementing partitioning methods (Range, Hash, and List).



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