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Job Description:
Senior Data Engineers for various and unanticipated worksites throughout the U.S. (HQ: Chicago, IL). Lead operational processes that produce reports and analytics for third-party end clients. Independently gather, transform, validate, aggregate, and report on client data. Perform data validation and data quality checks to enforce high data quality for operational tasks. Lead a team of junior data engineers to analyze data and systematically apply in-house developed, complex analysis technology to test the data quality and create benchmark solutions. Work with internal stakeholders to resolve issues in data quality. Responsible for meeting all SLAs to deliver high quality data in a timely and consistent manner. Recommend ways to improve data reliability, efficiency, and quality. Technical Environment: Python, SQL, Agile Methodologies, Scrum SDLC, Version Control using Git, AWS, financial analysis of credit card data, executing ETL pipelines, data cleaning, macro programing using MS Office, creation of dashboards for client reporting, relational databases, S3, Redshift, Postgre SQL, Dynamo DB, EC2, Data Lake formation, AWS Glue, Lambda, EMR, Cloud Formation.
Job Requirements:
Bachelor’s degree in Computer Science or related field plus 3 years of experience in Database Engineering or a related field required. Required skills: Python, SQL, Agile Methodologies, Scrum SDLC, Version Control using Git, AWS, financial analysis of credit card data, executing ETL pipelines, data cleaning, macro programing using MS Office, creation of dashboards for client reporting, relational databases, S3, Redshift, Postgre SQL, Dynamo DB, EC2, Data Lake formation, AWS Glue, Lambda, EMR, Cloud Formation. Telecommuting permitted.
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