Senior Data Operations Analyst (Python & SQL)
External
Nielseniq · Chennai, IndiaPrepare for this interview
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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, KPIs reporting, productivity initiatives, RCAs are the key areas of work for this team. Apart from this, the team is also responsible to analyze, classify and management of the data. 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 Experience with Python, 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. Must have work experience in SQL and Python Willing to work in Flexible shifts
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