Sr. Data Steward Alternatives - Madrid, España - Santander

Santander

Empresa verificada

Madrid, España

hace 3 semanas

Publicado por:

Isabel García

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Descripción

Sr. Data Steward Alternatives

Country:
Spain

WHAT YOU WILL BE DOING

Santander Asset Management is looking for a Data Steward Alternatives based in our Madrid office.

WHY YOU SHOULD CONSIDER THIS OPPORTUNITY

Santander Asset Management is a global structure with strong local roots in Europe and Latin America. With presence in 11 countries, we have assets of more than €175 billion* working for institutional clients, individual clients, and intermediaries such as Santander banks in all geographies. Our knowledge in Latin America makes us real experts on the region, allowing us to provide you with unique opportunities to invest. Our philosophy is to manage our investments to capture maximum upside but also downside protection. We offer a comprehensive range of investment solutions, from investment funds to illiquid assets, to provide right answers to your needs.

Santander is proud of being an organization where there are equal opportunities regardless of gender identity, culture and disability. Our mission is to contribute to help more people and business prosper.

We embrace a strong risk culture and all of our professionals at all levels are expected to take a proactive and responsible approach toward risk management.

WHAT YOU WILL BE DOING

As a
Data Steward Alternatives you will be responsible to coordinate and manage new Data initiatives and related projects by defining high-level business cases; provides requirements; tracks and prioritizes data projects within Asset Management Information Domain.

We need someone like you to help us in different fronts:

Manages new Data initiatives an related projects by defining high-level business cases; provides requirements; tracks and prioritizes data projects within domain.
Defines and validates business definitions to complete data artifacts for key data elements (KDEs) on Asset Management Information Domain. Design and complete Data Workflows, Business Glossary identification, Data Dictionary, Data Traceability, Defines Controls (data quality rules) and Data Quality KPIs.
Complete Root cause analysis to identify inconsistences about data events.
Translates business strategies into actionable businessoriented Data Management strategies for Asset Management Information Domain.
Designs reportings that delivers actionable databased insights for business units across the Company.
Manages the production and reporting for Data Quality (KPIs essential dashboards).
Manages the operating policies, and standards for the Chief Data Office Area.
Assembles project plans, procedures, teamwork assignments, monitors work effort daily, identifies resource needs, performs quality reviews, and escalates functional, quality, and timeline issues appropriately.
Enforces and ensures policies, practices and procedures are understood and followed by direct reports, customers, and stakeholders.
Sets goals and articulates objectives for team members in alligment with departmental objectives.
Manages independent Data Quality professionals.
Recommends changes to policies, procedures, limits, concentrations, and regulations based on data from analytical reporting.
Drives the success of tactical and strategic objectives with oversight and execution of analytical activities and data projects.
Determines official sources of data in scope. Define data workflows.

EXPERIENCE

35 years relevant experience as Senior Consultant.

EDUCATION

Finance, Management Information Systems, Statistics, or equivalent quantitative field.
Preferred: Master's Degree; Business Administration, Computer Science, Information Technology or equivalent quantitative field or equivalent work experience.
Preferred: Formal certification on Data Management tool (Data Quality
Data Governance).

SKILLS & KNOWLEDGE

Full Lifecycle Data Quality experience
Experience in migration of Data Management platforms
Ability to summarize big amount of data and derive insight from it
Experience in data remediation, Data Cloud, Data Lake
Familiarity with technical linage, data dictionary and data workflows (platform and appreciation)
Appreciation of the KDE (Key Data Elements) identification and link to Data Quality
Appreciation of data architecture
Comfortable with definition, implementation, and data operation aspects (controls Level 1, Level 2, KPIs)
Understanding of SLA metrics definition, monitoring and taking decisions based on this metrics
Advanced knowledge and experience using statistical packages for analyzingvisualization data sets (Excel, Access, Tableau, Power-Bi).