CVS Health Senior Data Engineer in Wellesley, Massachusetts
Participate in the design, build and management of large scale database structures and pipelines and efficient Extract/Load/Transform (ETL) workflows for Aetna Databases. Develop large scale data structures and pipelines to organize, collect and standardize data that helps generate insights and address reporting needs. Write ETL (Extract / Transform / Load) processes, design database systems and develop tools for real-time and offline analytic processing. Collaborate with the data science team to transform data and integrate algorithms and models into automated database processes. Work with Hadoop architecture, HDFS commands and experience designing & optimizing queries to build data pipelines. Work with programming skills including Python, Java, Hive, Spark, and MySQL to build robust data pipelines and dynamic systems. Develop framework for API based integrations for building models as Service architecture and allow integration with multiple external and internal system. Build tools and software to automate manual processes using technologies including Shell scripting, Java, Python & SQL. Build data marts and data models to support clients and internal customers. Integrate data from a variety of sources, ensuring that they adhere to data quality and accessibility standards.
Data & Analytics
Full or Part Time:
Percent of Travel Required:
Posting Job Title:
Senior Data Engineer
Primary Location (City, State):
Aetna is an Equal Opportunity, Affirmative Action Employer
Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
Minimum 5 years of experience developing large scale data structures and applications to organize, collect and standardize data. Experience developing systems to integrate with multiple external or internal applications leveraging Java/Python based Rest API integrations; working with Hadoop architecture and HDFS commands; utilizing advanced programming skills in languages including Java, Python, SQL, and Spark to build robust data pipelines and dynamic systems; identifying ways to improve data reliability, efficiency, and quality; and developing prototype products and working on Proofs of Concept to pick latest market tools and technologies quickly and add to product landscape to help build stable framework and product.
Benefit eligibility may vary by position.
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