Checking job availability...
Original
Simplified
Responsibilities
- data modeling: to model raw data into clean, tested, and reusable datasets.
- data transformation: apply various transformations to different data pieces to ensure they correspond to given tasks. transformations may include removing inaccurate or corrupted data; aggregating data items into a summarized version; filtering information to get rid of irrelevant, duplicated, or overly sensitive data; joining two or more database tables by their matching attributes; and splitting a single column into multiple ones, to name a few.
- data documentation: maintaining data documentation to ensure that everyone on the team uses the same definitions and language defining data quality rules, standards, and metrics: take responsibility for data quality management setting software engineering best practices for analytics: applying software engineering best practices
- data visualization: converting data into a suitable graphic format. This involves building dashboards, graphs, charts, and reports using BI tools
- close collaboration with other team members: to work collaboratively with all stakeholders namely data engineers, business analysts, and data scientists to align business requirements with data assets
- Bachelor degree in Computer Science, Mathematics, Statistics or related fields
- Fresh Graduate are welcome
- Collecting data, researching ,developing and implementing data- gathering methods
- Collaboration Mindset
- Data driven mindset with the ability to develop insightful reports, dashboards and presentations.
- Analytical mind with problem-solving attitude
- Firm understanding of statistics and database Ability to work in a fast-paced environment Strong communication skills Strong SQL, Python/R, dbt
- Strong logic at business and data.
Responsibilities
- data modeling: to model raw data into clean, tested, and reusable datasets.
- data transformation: apply various transformations to different data pieces to ensure they correspond to given tasks. transformations may include removing inaccurate or corrupted data; aggregating data items into a summarized version; filtering information to get rid of irrelevant, duplicated, or overly sensitive data; joining two or more database tables by their matching attributes; and splitting a single column into multiple ones, to name a few.
- data documentation: maintaining data documentation to ensure that everyone on the team uses the same definitions and language defining data quality rules, standards, and metrics: take responsibility for data quality management setting software engineering best practices for analytics: applying software engineering best practices
- data visualization: converting data into a suitable graphic format. This involves building dashboards, graphs, charts, and reports using BI tools
- close collaboration with other team members: to work collaboratively with all stakeholders namely data engineers, business analysts, and data scientists to align business requirements with data assets
- Bachelor degree in Computer Science, Mathematics, Statistics or related fields
- Fresh Graduate are welcome
- Collecting data, researching ,developing and implementing data- gathering methods
- Collaboration Mindset
- Data driven mindset with the ability to develop insightful reports, dashboards and presentations.
- Analytical mind with problem-solving attitude
- Firm understanding of statistics and database Ability to work in a fast-paced environment Strong communication skills Strong SQL, Python/R, dbt
- Strong logic at business and data.