Data Engineer

This is a remote position.

• Develop, implement, support, and operationalize AWS data lake infrastructure & services
  
• Create and maintain optimal data pipeline architecture, 
  
• Develop, implement, support to enhance infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, ETL (e.g., Informatica Cloud) AWS ‘Data Lake’ technologies (Glue, Lambda Functions, Step Functions, HVR).
  
• Build analytics tools that utilize the data pipeline to provide actionable insights into patient care, operational efficiency and other key business performance metrics.
  
• Support to enhance a deep understanding of AWS’s v​ast data sources and know exactly how, when, and which data to use to solve business problems.
  
• Monitor and maintain data lake security and data lake services.
  
• Manage numerous requests concurrently and strategically, prioritizing when necessary
  
• Troubleshoot technical issues and provide solutions and fixes using various tools and information such as server logs and report debug logs.  General and administrative tasks of AWS ETL handling
  

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Mathematics, or a related discipline.
  
• 4-10 (+/-) years of experience for various position in Information Technology within a complex, matrixed, and global business environment.
  
• Experience with Agile framework and DevOps.  3-6 (+/-) years of experience in building ETL data pipelines using AWS Glue and Pyspark, Lambda Functions
  
• Exception Handling and performance optimization techniques on python/pyspark scripts with some experience with REST API services would added advantage
  
• Experienced as a data engineer with AWS Data Lake Technologies and Services Expert working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
  
• Building and optimizing AWS ‘Data Lake’ data pipelines, architectures, and data sets.
  
• Strong analytic skills related to working with unstructured datasets.
  
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
  
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets.
  
• Understanding of message queuing, stream processing, and highly scalable AWS ‘Data Lake’ data stores.
  
• Understanding of database and analytical technologies in the industry including MPP and NoSQL databases (e.g., Snowflake, Redshift), Data Warehouse design, ETL, BI reporting and Dashboard development
  

Benefits

• Professional certifications e.g., AWS Certified solution architect, etc.
  
• AWS data lake administrations
  
• Good documentation and interpersonal relationship skills
  
• Strong written and verbal communicaton skills.