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 businesses 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 for coordinating and managing new Data initiatives and related projects by defining high-level business cases; providing requirements; tracking and prioritizing data projects within the Asset Management Information Domain. We need someone like you to help us in different fronts:
Manages new Data initiatives and related projects by defining high-level business cases; provides requirements; tracks and prioritizes data projects within the domain.
Defines and validates business definitions to complete data artifacts for key data elements (KDEs) on Asset Management Information Domain. Designs and completes Data Workflows, Business Glossary identification, Data Dictionary, Data Traceability, Defines Controls (data quality rules) and Data Quality KPIs.
Completes Root cause analysis to identify inconsistencies about data events.
Translates business strategies into actionable business-oriented Data Management strategies for Asset Management Information Domain.
Designs reportings that deliver actionable data-based 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 alignment 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
3-5 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 large amounts of data and derive insight from it
Experience in data remediation, Data Cloud, Data Lake
Familiarity with technical lineage, 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 these metrics
Advanced knowledge and experience using statistical packages for analyzing-visualization data sets (Excel, Access, Tableau, Power-Bi).
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