Sr. Data Engineer

CVS Health•Woonsocket, RI

4d•$130,832 - $166,860•Hybrid

About The Position

Caremark LLC, a CVS Health company, is hiring for the following role in Woonsocket, RI: Sr. Data Engineer to Develop, build and manage large-scale data structures, pipelines and efficient Extract/Load/Transform (ETL) workflows to address complex problems and support business applications. Duties include: develop large scale data structures and pipelines to organize, collect and standardize data to generate insights and addresses reporting needs; write ETL (Extract/Transform/Load) processes, design database systems, and develop tools for real-time and offline analytic processing that improve existing systems and expand capabilities; collaborate with Data Science team to transform data and integrate algorithms and models into automated processes; test and maintain systems and troubleshoot malfunctions; leverage knowledge of Hadoop architecture, HDFS commands, and designing and optimizing queries to build data pipelines; utilize programming skills in Python, Java, or similar languages to build robust data pipelines and dynamic systems; build data marts and data models to support Data Science and other internal customers; integrate data from a variety of sources and ensure adherence to data quality and accessibility standards; analyze current information technology environments to identify and assess critical capabilities and recommend solutions to complex business problems; and experiment with available tools and advise on new tools to provide optimal solutions that meet the requirements dictated by the model/use case. Telecommuting available. Multiples positions.

Requirements

Master’s degree (or foreign equivalent) in Computer Science, Data Science, Statistics, Mathematics, Analytics, or a related field and one (1) year of experience in the job offered or related occupation.
One (1) year of experience in Software development best practices.
One (1) year of experience in Data analytics on large data sets in healthcare, business, or retail sector.
One (1) year of experience in Java, Python, or R.
One (1) year of experience in Agile methodologies or SAFe Software Development Principles.
One (1) year of experience in Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP).
One (1) year of experience in SQL or SAS.
One (1) year of experience in Spark, PySpark, or Scala.
One (1) year of experience in Databricks.
One (1) year of experience in Extract/Transform/Load (ETL) processes.
One (1) year of experience in Cloud components including cluster management.
One (1) year of experience in Contributing to large-scale applications development, data science, or data analytics projects.
One (1) year of experience in Designing data architectures, including data pipelines, distributed computing engines, and machine learning infrastructure design.
One (1) year of experience in Healthcare data management processes and techniques, including data standards, interoperability, and proper data privacy.

Responsibilities

Develop, build and manage large-scale data structures, pipelines and efficient Extract/Load/Transform (ETL) workflows to address complex problems and support business applications.
Develop large scale data structures and pipelines to organize, collect and standardize data to generate insights and addresses reporting needs.
Write ETL (Extract/Transform/Load) processes, design database systems, and develop tools for real-time and offline analytic processing that improve existing systems and expand capabilities.
Collaborate with Data Science team to transform data and integrate algorithms and models into automated processes.
Test and maintain systems and troubleshoot malfunctions.
Leverage knowledge of Hadoop architecture, HDFS commands, and designing and optimizing queries to build data pipelines.
Utilize programming skills in Python, Java, or similar languages to build robust data pipelines and dynamic systems.
Build data marts and data models to support Data Science and other internal customers.
Integrate data from a variety of sources and ensure adherence to data quality and accessibility standards.
Analyze current information technology environments to identify and assess critical capabilities and recommend solutions to complex business problems.
Experiment with available tools and advise on new tools to provide optimal solutions that meet the requirements dictated by the model/use case.