Aws Data Engineer

Job Overview

• Work closely with Business Intelligence Analysts and Stakeholders to identify reporting needs, metrics, data assets and systems.
• Support the modeling and creation of datasets using AWS Infrastructure (Glue, Lambda), Python, SQL to be then used for self-service dashboard reports.
• Build knowledge about all the datasets inside the data lake to be able to provide guidance to other engineers and/or stakeholders
• Streamline data preparation and processes for maximum automation and efficiency whilst supporting environment migrations where required
• Analyze, organize, segment, and disseminate raw or unprocessed data based on business needs.
• Be the key anchor for data extraction, preparation, and hosting processes.
• Create master data files from disparate data sources by building data pipeline
• Develop and test architecture for data extraction
• Provide continuous connectivity to a master data source and access to refreshed data
• Ensure data quality and reliability
• Data expert for datasets

What your background should look like:

• 3+ years of Data Engineering experience in ETL design, development, optimization & testing using SQL, Python, AWS Services (Lambda, Glue, Redshift, S3)
• 3+ Complex SQL Tuning, Stored Procedures, Data Warehousing best practices etc.
• 3+ years of experience in relational or Cloud database design, optimization, and performance; preferably with AWS Redshift/Aurora, SAP HANA, and Oracle.
• Strong problem-solving capabilities. Results oriented. Relies on fact-based logic for decision-making.
• Experience with creation of solution, project documentation
• Ability to work with multiple projects and work streams at one time. Must be able to deliver results based upon project deadlines.
• Willingness to flex daily work schedule to allow for time-zone differences for global team communications.
• Strong interpersonal and communication skills.

Competencies