Job description
Project Role : Data Modeler
Project Role Description : Work with key business representatives, data owners, end users, application designers and data architects to model current and new data.
Must have skills : Google BigQuery
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary: As a Data Modeler, you will engage with key business representatives, data owners, end users, application designers, and data architects to model both current and new data. Your typical day will involve collaborating with various stakeholders to understand their data needs, analyzing existing data structures, and designing effective data models that support business objectives. You will also be responsible for ensuring that the data models are aligned with best practices and meet the requirements of the organization, facilitating smooth data integration and accessibility across different platforms. Roles & Responsibilities: - Expected to be an SME.
- Collaborate and manage the team to perform.
- Responsible for team decisions.
- Engage with multiple teams and contribute on key decisions.
- Provide solutions to problems for their immediate team and across multiple teams.
- Facilitate training sessions for junior team members to enhance their understanding of data modeling.
- Continuously evaluate and improve data modeling processes to increase efficiency and effectiveness. Professional & Technical Skills: - Must To Have Skills: Proficiency in Google BigQuery.
- Good To Have Skills: Experience with data warehousing concepts and ETL processes.
- Strong understanding of data modeling techniques and methodologies.
- Familiarity with SQL and data querying languages.
- Experience in working with cloud-based data solutions. Additional Information: - The candidate should have minimum 5 years of experience in Google BigQuery.
- This position is based in Mumbai.
- A 15 years full time education is required.
This job post has been translated by AI and may contain minor differences or errors.
