Major Responsibilities: Understand the business and partner with leaders from operation, product, architects and dev to source, transform and build datasets into AWS data technology solutions. Design, develop and analysis of data architecture and data warehouse approaches. Design and build new data processes for modeling, data mining, and production purposes. Monitors current DBMS performance, develops procedures and improve the DBMS environment. Monitors current data warehouse performance, build SLA alerts and improve the data warehouse performance. Build and maintain the infrastructure required for optimal ETL process (extraction, transformation and loading of data) from a wide variety of data sources using SQL and AWS technologies. Empower and assist operation and product teams through building key data sets and data-based recommendations. Lead reporting and insights automation initiative, responsible for leading the efforts of scoping, planning, delivering automatic business intelligence reports and customer insights. Bring focus and attention to the future of the platform in the cloud and open new data technology possibilities there. Responsible for ensuring that the technical output of the Data Engineering team conforms to best practices and standards. Perform and interpret data studies and product experiments concerning new data sources or new uses for existing data sources. Automating reports/Analysis and authoring pipelines via SQL/python based ETL framework.

Job Requirements: Applicant must possess a Master’s degree or foreign equivalent in Computer Science, Information Systems or related field and 2 years of experience in the data engineering, data warehousing, Business Intelligence, or closely related field. In the alternative, employer will accept: Bachelor’s degree or foreign equivalent in Computer Science, Information Systems or related field and 5 years of experience in the data engineering, data warehousing, Business Intelligence, or closely related field. Additionally, the applicant must have 2 years of professional experience in the following: 1.) Database: Expertise in Relational and Non-Relational Database, familiar with MySQL,MongoDB, MS SQL Server, Redis; 2.) Database systems in general (Foreign keys, indexes, basic DBA tasks); 3.) Data Warehouse (RedShift); 4.) ETL best practices and data engineering; 5.) Performance tuning and query optimization; 6.) Developing solution within AWS Services framework (EC2, RDS, Lambda.); 7.) Large scale data processing using traditional and distributed systems like Hadoop, Spark, and Airflow; 8.) Python or other scripting languages; and 9.) Team Management.