Cloud Engineer Senior

Job Title

Your work falls into two primary categories:

Strategy Development and Implementation

• Develop data filtering, transformational and loading requirements
• Define and execute ETLs using Apache Spark on Hadoop among other Data technologies
• Determine appropriate translations and validations between source data and target databases
• Implement business logic to cleanse & transform data
• Design and implement appropriate error handling procedures
• Develop project, documentation and storage standards in conjunction with data architects
• Monitor performance, troubleshoot and tune ETL processes as appropriate using tools like in the AWS ecosystem.
• Create and automate ETL mappings to consume loan level data source applications to target applications
• Execution of end to end implementation of underlying data ingestion workflow.

Operations and Technology

• Leverage and align work to appropriate resources across the team to ensure work is completed in the most efficient and impactful way
• Understand capabilities of and current trends in Data Engineering domain

Qualifications

• At least 5 years of experience developing in Java, Python
• Bachelor’s degree with equivalent work experience in statistics, data science or a related field.
• Experience working with different Databases and understanding of data concepts (including data warehousing, data lake patterns, structured and unstructured data)
• 3+ years’ experience of Data Storage/Hadoop platform implementation, including 3+ years of hands-on experience in implementation and performance tuning Hadoop/Spark implementations.
• Implementation and tuning experience specifically using Amazon Elastic Map Reduce (EMR).
• Implementing AWS services in a variety of distributed computing, enterprise environments.