Amazon Quick Sight Data Engineer/Lead Data Analytics Engineer

Must have

3+ years' experience in Amazon Quick Sight and SQL.

1+ years of experience with Qlik Sense.

3+ year of experience with Amazon Quick Sight for creating data sets, dashboards and visualizations.

3+ years of experience in SQL data manipulation and analysis.

1+ year of experience with Qlik Sense for creating data sets, dashboards and visualizations.

Required:

Bachelors or Master's degree in a Relevant Field such as: Data Science, Business Analytics, Information Systems, Computer Science.

6+ years of progressively increasing professional experience in Data Analytics, with at least:

3+ years in a senior level role.

3+ years' experience in Amazon Quick Sight and SQL.

1+ years of experience with Qlik Sense.

3+ year of experience with Amazon Quick Sight for creating data sets, dashboards and visualizations.

3+ years of experience in SQL data manipulation and analysis.

1+ year of experience with Qlik Sense for creating data sets, dashboards and visualizations.

Experience working closely with stakeholders to understand needs and define analytic requirements.

Experience with data warehousing concepts and ETL processes.

Cloud Computing and AWS experience.

Excellent communication and collaboration, analytical and problem-solving skills.

Creativity and innovative thinking.

A credit check is required as a pre-employment screening.

Responsibilities:

Provide strategic oversight and technical leadership for the migration of data analytics assets from Qlik Sense to Amazon Quick Sight.

Strategically analyze and deeply understand existing reports and data models in Qlik Sense.

Lead the design and development of equivalent reports and data models in Amazon Quick Sight.

Ensure data accuracy and consistency during the report migration process.

Optimize the new reports for performance and usability on the Quick Sight platform.

Oversee the testing and validation of migrated reports against the original Qlik Sense versions.

Document the migration process comprehensively and provide expert training/support to end-users.

Collaborate effectively with data engineers, analysts, and business stakeholders to drive a successful migration project.

Identify opportunities for process improvements and innovative solutions to enhance the overall data analytics capabilities.