AWS Data Engineer - Python (5-15 yrs)

Responsibilities include :

- 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

Qualifications and skills required :

- 5+ 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.

- 5+ 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.