Data Quality Lead

hace 1 mes

Guadalajara, México AstraZeneca A tiempo completo

**Positions are open to Mexican Citizens and official residents of Mexico.**
**Location: Guadalajara (hybrid)**
**Strong English interpersonal skills required**:
**About the AstraZeneca**:
**AstraZeneca is a global, science-led, patient-focused pharmaceutical company that focuses on the discovery, development, and commercialization of prescription medicines for some of the world’s most serious disease. But we’re more than one of the world’s leading pharmaceutical companies. At Astra Zeneca, we’re dedicated to being a Great Place to work**:
**Data Quality is the primary driver of operations for the Data & Analytics Organization. Working to design and facilitate the DQM processes and tools, they contribute directly to the business processes AstraZeneca. The data quality analyst works directly with various data consumers and contributors, ensuring that Data quality is measured and managed. A wide variety of tasks and responsibilities provide exposure to multiple business processes, operating units, and business data that will give the professional a solid foundation of knowledge for future career growth and development at AstraZeneca.**:
**The data quality lead along with the rest of the D&A Axial team, will work to achieve the AstraZeneca D&A vision by elevating master data management and governance.**:

- ** Supporting design and implementation of Axial data quality processes and tools**:

- ** Measuring data quality for all governed master data objects (material, vendor, customer, finance objects and others) and ensure the updates are appropriate, authorized, and documented as well as in compliance with overall master data governance framework and standards, SLAs, policies, and procedures.**:

- ** Collecting and managing data standards and business rules and related KPIs**:

- ** Managing a team of data quality and master data analyst**:

- ** Data Cleansing**:

- ** Providing Training**:

- ** Providing Business Support (DQM Tools): Answering business support requests via the DQM support platform. Execution of support policies and standards.**:

- ** Mass Data Changes**:

- ** Analyzing data feeds and reconcile reports which are critical to daily operations as well as ensure compliance with data privacy.**:

- ** Facilitating DQM Processes: Monitoring and coordinating maintenance processes. Identifying and resolving bugs. Supporting identification of rule changes in the DQM Tool**:
**Requirements**:

- ** Minimum Bachelor's degree in business or a technical discipline, or equivalent level of experience in a data analysis/administration, data quality, data governance, or related field**:

- ** 3 -6 years of relevant professional experience in data quality management**:

- ** Excellent understanding of the business impact of data and data quality**:

- ** Profound understanding of modern data quality management concepts**:

- ** Affinity and interest for data quality and governance topics**:

- ** Meticulous approach of working and attention to detail**:

- ** Good communication skills and proficiency in Microsoft Office products**:

- ** Decisive when faced with multiple options or methods for solving problems or creating solutions**:

- ** Ability to work in a deadline driven environment**:
**Desirable**:

- ** 5+ years of experience in the Data Quality Management**:

- ** Experience in SAP ECC or S4/HANA**:

- ** Good understanding of SAP MDG**:

- ** Experience with DQM tools and data catalogues**:

- ** Pharmaceutical Industry or shared services experience**:
**When we put unexpected teams in the same room, we ignite ambitious thinking with the power to inspire life-changing medicines. In-person working give us the platform we need to connect, work at pace and challenge perceptions. That’s why we work, on average, a minimum of three days per week from the office. But that doesn’t mean we’re not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our outstanding and bold world.**:

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