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Accept ClosePress Tab to Move to Skip to Content LinkSearch by KeywordSearch by LocationSearch by KeywordSearch by LocationLoading...Team:LocationType:Grade:Create Alert\xc3\x97Select how often (in days) to receive an alert:StartPlease wait...Data Quality AnalystAt adidas, our love for sport drives who we are and what we do. But just as a ball is more than leather and thread, and a show more than padding and plastic, we are bigger than our products. We don\'t just work to create faster shoes and lighter fabrics. We strive to help athletes everywhere perform their best. We believe that it\'s hard work inventing the future of sport, and that\'s why we love it; that when you push your limits, you make it possible for others to push theirs.We believe that through Sport, we have the power to change lives.To change lives, we have to create direct relationships with consumers and the best way to accelerate building direct relationships is through Digital.Data Quality AnalystadidasPurpose & Overall Relevance for the Organization:As a Data Quality Analyst at adidas you will support the EU eCom Analytics team in ensuring top notch Data Quality of the EU eCom data present on our Databricks Lakehouse Platform. You will be based out of our Tech Hub in Gurugram, India with around 20 other colleagues from the same team (data engineers, data scientists and data analysts) and hundred more from other adidas departments. You will be part of a highly engaged, multinational agile team, in charge of creating and enhancing digital data products, reporting directly into the Analytics Data Product Owner based in Amsterdam, Netherlands. Together with the Analytics Data Product Owner you will draft a robust Data Quality Framework including Incident Handling, Service Level Agreements and Prioritization Matrix. You will ensure that the incidents coming in are assigned and prioritized according to the defined Data Quality Framework and that systemic improvements are implemented based on observed recurring Data Quality issues. You will also help with backlog management during the Sprint Planning together with the Data Foundation engineering team. And follow up with the upstream dependent team to resolve tickets and identify root cause. Your work will be instrumental in ensuring accurate and reliable data to adidas EU eCom Analytics teams who provide all the business insights driving our Eu eCom business top and bottom line. As a team we believe in collaboration and high-energy. You benefit from flat hierarchies and will be exposed to various organizational levels. Our team has practiced a hybrid working model for several years, so you will have no issues with fitting in and becoming a valued member in no time.Key Responsibilities:1. Incident Root Cause Analysisa. Investigate cause(s) of Incidents,b. Coordinate with dependent team to identify root cause(s) of Incidents.2. Incident Resolutiona. Work with the Data Engineers to address issues in our scope,b. Coordinate with dependent teams to resolve issues outside of our scope.c. Track progress across the board.3. Ticket Traffic Managementa. Manage all tickets coming in our dedicated JIRA board,b. Ensure tickets are clear and contain all needed information, labels, components etc.,c. Assign tickets to relevant team members to work on,d. Track all issues impacting EU eCom data (whether dependent on other teams or only on our team), e. Communicate status and resolution to stakeholders.4. Backlog Managementa. Prioritize tickets according to defined Prioritization Matrix and Service Level Agreements,b. Refine requirements and participate in sprint planning,c. Coordinate with the Product Owner to ensure tickets are prioritized accordingly into the Data Engineering backlog.5. Data Quality Long Term Improvementa. Ensure we always improve our Data Quality rules to capture recurring issue that may surface over Incidents,b. Maintain the existing rules and ensure they are working as intended,c. Create and Maintain Data Quality dashboards,d. Provide ad-hoc demo on existing Data Quality dashboards and rules,e. Stay at the forefront of innovation in the data quality space and research/test/leverage new technologies, together with the Analytics Data Product Owner, for improved outcomes.Key Relationships:
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