Jll
real estate
DataQualityandGovernanceAnalyst1
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Quality and Governance Analyst 1 at Jll. Skills: Data Quality, Data Governance, Data Validation, Data Deduplication, Data Remediation, Reporting, SQL, Python. Ensuring the quality, accuracy, and integrity of data within our real estate databases.. Performing data validation, deduplication, and remediation activities.”
Industry & Context.
Excellent problem-solving skills; Identifying issues and developing effective solutions.
What They're Looking For.
Must Have
Bachelor’s/Master’s degree in information systems, Business, Data Science, or related field., Proficiency in data analysis tools such as Advanced Microsoft Excel, VBA, Power Query, SQL, Python, Data bricks or similar., Knowledge on data visualization tools (e. g. , Tableau, Power BI), Familiarity with data validation tools and techniques, especially for business entities (e. g. , D&B Hoovers)., understanding of critical data elements and data quality principles., Experience in validating company information from external sources., Knowledge of primary-subsidiary company relationships and organizational hierarchies., Excellent problem-solving skills and attention to detail., communication skills, both written and verbal, for interacting with stakeholders., Ability to work independently and prioritize tasks in a fast-paced environment.
Nice to Have
Experience with CRM and/or data governance tools is a plus., Experience in the real estate industry or a similar domain., Familiarity with data governance frameworks and processes., Experience working in a data stewardship role.
What You'll Do.
and integrity of data within our real estate databases.
Performing data validation
and remediation activities.
Conducting comprehensive research and validation using authoritative sources like the company website and D&B Hoovers.
Analysing and updating the relationships between primary and subsidiary companies.
Perform validation of company information including names
and other key attributes.
Utilize company websites
and other reliable sources to verify the accuracy of data.
Ensure critical data elements meet quality standards before they are used by stakeholders.
Validate and enrich missing data attributes with verified information.
Conduct data analysis to identify and eliminate duplicate company records in the database.
Use fuzzy matching techniques to detect potential duplicate companies and assess their validity.
Implement automated and manual deduplication processes to maintain a clean and reliable database.
Investigate data discrepancies and work with internal stakeholders to resolve issues.
Update and correct erroneous data points
including incorrect addresses
and business identifiers.
Ensure records are accurately maintained and are consistently monitored for compliance with business standards.
and maintain reporting systems and dashboards.
Create and update documentation for processes
and interpret data from multiple sources.
Prepare regular and ad-hoc reports for various stakeholders.
Ensure accuracy and consistency of all reports and documentation.
Collaborate with different departments to understand their reporting needs.
Develop and implement documentation standards and best practices.
Train staff on proper documentation techniques and reporting procedures.
Maintain a centralized repository for all reports and documentation.
Continuously improve reporting processes and documentation quality
Ensure compliance with relevant regulations and internal policies.
Assist in audit preparations by providing necessary reports and documentation.
How You'll Work.
Team & Collaboration
Collaborate with data stewards, analysts, and stakeholders to gather data requirements and align quality initiatives with business needs.; Participate in meetings with stakeholders to discuss data quality issues.; Work with IT teams to implement tools and processes that facilitate data quality improvements.; Collaborate with cross-functional teams to ensure stakeholder needs are addressed.
Communication Scope
Clear and effective verbal and written communication.; communication skills, both written and verbal, for interacting with stakeholders.
Full Job Description
**JLL empowers you to shape a brighter way**. Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward. **Job Title – Data Quality and Governance Analyst 1** **Location – Bangalore, Karnataka** **Department – Data Quality and Assurance, JLLT CoE** **Reports To - Data Quality & Governance Manager ** **What this job involves:** **About the role** _**#JLLTechAmbitions**_ The Data Quality Analyst will be responsible for ensuring the quality, accuracy, and integrity of data within our real estate databases. This role includes performing data validation, deduplication, and remediation activities. The ideal candidate will possess a solid understanding of critical data elements and will conduct comprehensive research and validation using authoritative sources like the company website and D&B Hoovers. They will also be responsible for analysing and updating the relationships between primary and subsidiary companies, ensuring accurate and actionable data for business stakeholders. The ideal candidate will possess an advanced understanding of critical data elements, engage in complex data analysis, support strategic projects aimed at data governance improvements. **Responsibilities** **Data Validation** Perform validation of company information including names, addresses, websites, and other key attributes. Utilize company websites, D&B Hoovers, and other reliable sources to verify the accuracy of data. Ensure critical data elements meet quality standards before they are used by stakeholders. Validate and enrich missing da
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