Data Governance Analyst

NielsenIQ

Vadodara

Presencial

INR 1.200.000 - 1.800.000

Jornada completa

Hace 8 días

Una candidatura completa en un minuto

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Ventajas ofrecidas por este puesto de trabajo

Flexible working environment
Volunteer time off
LinkedIn Learning
Employee-Assistance-Program (EAP)

Descripción de la vacante

NielsenIQ is seeking a data governance professional to bridge the Supplier Engagement team with Ops pillars, focusing on data quality, BAU activities, and data flow across retailers and vendors. The role involves managing data reminders, data receipt, and addressing quality checks across multiple systems.

The candidate will coordinate system changes, MSD ticket tracking, and KPI reporting, while supporting data analysis and transformation across large data sets and formats.

Formación

  • Experience with Python, FoxPro, and Cloud Platforms.
  • Large data handling skills with exposure to multiple formats and TLog data.
  • Understanding of SAP and transactional data handling.
  • FTP and MFT setup and maintenance.
  • Ability to extract, transform, load, and clean large data sets from multiple sources.

Responsabilidades

  • Act as internal SPOC for Ops and regional leadership teams; provide KPI updates and BAU progress.
  • Collaborate on retailer onboarding, data quality tracking, and change management for data receipt.
  • Address data corrections and MSD ticket resolution with retailer discussions and planning.
  • Coordinate with Input/Output for processing reissued data and store information changes.
  • Conduct quality checks, RAP scoring, and eDive data validation.

Conocimientos

Python
FoxPro
Cloud Platforms
SAP

Herramientas

FTP
MFT
Unix/Python queries
Excel

Descripción del empleo

Data Governance Job Description

eData Governance Job Description This role covers the activities post inputs are received from the source - retailers/vendors. Primary focus is to be the bridge between the Supplier Engagement team and other Ops pillars. System change surveys, BAU query resolution, MSD tickets tracking and closure, KPIs reporting, productivity initiatives, RCAs are the key areas of work for this team. Apart from this, the team is also responsible to analyze, clasify and management of the data. This role is accountable for BAU activities related to data, including data reminders, data receipt from retailers, and handling data queries arising from quality checks (RAP & DQI scoring).

Retailer Onboarding and Engagement

Collaborate with the Supplier Engagement Lead on retailer onboarding. Ensure compliance for received data by working closely with retailers and NielsenIQ teams. Track retailer or vendor data quality and conduct regular reviews with internal stakeholders and retailers. Drive specific quality improvement goals for retailers, including change management related to data receipt. Handle large data sets with exposure to multiple formats and TLog data. Understanding of SAP, transactional data handling, FTP, and MFT setup and maintenance. Ability to extract, transform, load, and clean large data sets from multiple sources. Familiarity with managing, querying, and aggregating large data sets.

System Change and Data Corrections

Plan and follow up on operational activities. Address data corrections due to MSD or other data errors through retailer discussions and planning with Ops. Track and resolve MSD tickets. Collaborate with INS team on results of eDive for System change

Stakeholder Management & BAU Collaboration and Communication

Act as the internal SPOC for Ops and regional leadership teams. Provide updates on KPIs, market progress on retailer onboarding, BAU KPIs, and productivity initiatives. (internal SPOC for Ops) Send data reminders and manage data receipt from retailers. Communicate with internal and external stakeholders to resolve data issues. Provide timely updates and visibility to stakeholders. contact data providers via email if data has not been received as per SLAs. Communicate with data providers on any discrepancies found in initial data checks, FoVa reports, shop usability, or other factory processes. Handle new store information and confirmation on store closures. Address new stores and closed store queries. Coordinate with Input Ops and Output for processing reissued data. Send relevant IO communications (internal) regarding new/closed stores, missing retailer data, estimation of retailer data, reissue of retailer data, store name changes, store mapping corrections, retailer expansion, and retailer data changes during BAU.

Quality Assurance

Conduct quality checks, including eDive primary testing of data, and RAP scoring, eDive Address data queries arising from quality checks.

Opportunity Identification

Identify new operational effecient opportunities within existing retailers. Ops teams (NOC), and DA Analysts to realize these opportunities, consulting closely with the commercial or RV team as applicable.

Qualifications

Experience with Python, FoxPro, and Cloud Platforms. Large data handling skills with exposure to multiple formats and TLog data. Understanding of SAP and transactional data handling. FTP and MFT setup and maintenance. Ability to extract, transform, load, and clean large data sets from multiple sources. Familiarity with managing, querying, and aggregating large data sets. Strong analytical and problem-solving skills. Proficient in complex business process modeling and data modeling concepts. Strong knowledge of Microsoft Office Suite (Excel, Word, Access, Outlook, PowerPoint). Extensive knowledge in Retail, specifically in POS and supply chain. Understanding of factory processes. Extensive knowledge in Retail, specifically in POS and supply chain. Proficiency in developing Unix/Python queries.

Experience with Python, FoxPro, and Cloud Platforms. Large data handling skills with exposure to multiple formats and TLog data. Understanding of SAP and transactional data handling. FTP and MFT setup and maintenance. Ability to extract, transform, load, and clean large data sets from multiple sources. Familiarity with managing, querying, and aggregating large data sets. Strong analytical and problem-solving skills. Proficient in complex business process modeling and data modeling concepts. Strong knowledge of Microsoft Office Suite (Excel, Word, Access, Outlook, PowerPoint). Extensive knowledge in Retail, specifically in POS and supply chain. Understanding of factory processes. Extensive knowledge in Retail, specifically in POS and supply chain. Proficiency in developing Unix/Python queries.

Experience with Python, FoxPro, and Cloud Platforms. Large data handling skills with exposure to multiple formats and TLog data. Understanding of SAP and transactional data handling. FTP and MFT setup and maintenance. Ability to extract, transform, load, and clean large data sets from multiple sources. Familiarity with managing, querying, and aggregating large data sets. Proficient in complex business process modeling and data modeling concepts. Strong knowledge of Microsoft Office Suite (Excel, Word, Access, Outlook, PowerPoint). Extensive knowledge in Retail, specifically in POS and supply chain. Understanding of factory processes. Extensive knowledge in Retail, specifically in POS and supply chain. Proficiency in developing Unix/Python queries.

Master's Degree or technical institute degree/certificate in statistics or data analytics, or equivalent work experience. 3+ years of relevant professional work experience. Understanding of various data and file formats. Ability to interpret different data structures and mapping. Flexibility to work according to local time zones and follow country holidays for supported countries. Strong technical knowledge and business interpretation of data. General systems understanding from an ETL point of view. Fluent in English; local market language skills (if required by markets).

Master's Degree or technical institute degree/certificate in statistics or data analytics, or equivalent work experience. 3+ years of relevant professional work experience. Understanding of various data and file formats. Ability to interpret different data structures and mapping. Flexibility to work according to local time zones and follow country holidays for supported countries. Strong technical knowledge and business interpretation of data. Strong analytical and problem-solving skills. Fluent in English; local market language skills (if required by markets). Extensive knowledge in Retail, specifically in POS and supply chain. General systems understanding from an ETL point of view.

Experience with Python, FoxPro, and Cloud Platforms. Large data handling skills with exposure to multiple formats and TLog data. Understanding of SAP and transactional data handling. FTP and MFT setup and maintenance. Ability to extract, transform, load, and clean large data sets from multiple sources. Familiarity with managing, querying, and aggregating large data sets. Proficient in complex business process modeling and data modeling concepts. Strong knowledge of Microsoft Office Suite (Excel, Word, Access, Outlook, PowerPoint). Understanding of factory processes. Extensive knowledge in Retail, specifically in POS and supply chain. Proficiency in developing Unix/Python queries.

Number and speed of resolving MSD tickets/BAU inqueries and closed / answered Operational Stability - Timely escalations, Risk flagging and Mitigation (Implementation Delays)

Additional Information Note

Role is at level 3

Our Benefits
  • Flexible working environment
  • Volunteer time off
  • LinkedIn Learning
  • Employee-Assistance-Program (EAP)

NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://nielseniq.com/global/en/info/niqs-ai-safety-policies/

About NIQ

NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights-delivered with advanced analytics through state-of-the-art platforms-NIQ delivers the Full View. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com

Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook

Our commitment to Diversity, Equity, and Inclusion

At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact.

To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion

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