Enterprise Data Steward

First Command Financial Services, Inc.•Fort Worth, TX

4d•Hybrid

About The Position

The role of the Enterprise Data Steward is to identify, investigate, and communicate data quality issues in enterprise applications while safeguarding against data loss. Data stewards also guide decision makers in determining where to place and consume specific data while considering business purposes, and how the location of certain data will incur risks. The Enterprise Data Steward leads organizational data governance activities, understands, and represents the data requirements of the business on IT projects, and are key implementers and enforcers of data policy, process, procedures, and standards set by the Data Governance Steering Committee. The Enterprise Data Steward is expected to lead a team of Data Stewards that prevent data quality issues by identifying frequent user errors, identifying aging technology, and working with business units to strengthen user competence.

Requirements

BA required or equivalent experience may be considered; MBA or MS or equivalent a plus.
10+ years of applied experience in Data Governance or comparable positions that handle data definitions, requirements gathering and fostering business partner relationships
Experience mentoring others and leading small teams
Strong understanding of relational and no sql data base concepts
Strong understanding of Data Governance and Data Quality
Strong understanding of methods to document data mapping and data lineage
Strong understanding in metadata management and data quality methodology
Strong data analysis skills with proficiency in SQL with knowledge of T-SQL and PL/SQL
Applied experience with cloud data solutions; Microsoft Azure a plus
Strong understanding of data management and data architecture practices
Applied experience with Data Governance and Quality tools (e.g., Collibra, Informatica, Purview, Talend, Aperture)
Applied experience with Agile frameworks; SAFe, KANBAN or SCRUM a plus
Applied experience documenting business definitions of technical assets and how data is organized within an organization
Applied experience transforming manual processes to industry standards
Comfort with ambiguity and proven ability to generate innovative solutions
Ability to be a self-starter and take initiative to achieve tangible results from a conceptual strategy

Nice To Haves

Financial services industry experience or other highly regulated industry experience a plus
Certifications related to Data Governance, Microsoft Azure, and/or Agile frameworks a plus
Applied experience with Salesforce CRM a plus
Applied experience in data visualizations and dashboards
Applied experience in managing End User Computing (EUC) Applications

Responsibilities

Champion and Establish Data Governance policies and methods to monitor adherence to policies.
Define the best practices and shape of the Data Catalog
Reporting on Enterprise Data Quality Score and escalating blocked or large data quality resolutions needing management attention
Manage Data Steward work and Data Domain assignments; Placing Data Stewards in positions to deliver their best work, while balancing the needs of the business
Establish technical data stewardship by defining the technical assets critical to our business processes, their meaning & relevance, establish lineage, and define workflows to manage our data;
Ensure that new systems, applications, and data integration measures adhere to existing data management practices, policies, and procedures.
Author data quality rules that consider criticality and usage of data
Identify and ensure the long term resolution of data quality issues, such as uniqueness, integrity, accuracy, consistency, and completeness, in a cost-effective and timely manner.
Generate data quality statistics and communicate to Data and Solution Owners
Devise, coordinate, and conduct mass data-cleansing initiatives for the purpose of purging and eliminating corrupt or redundant information
Identify causes of poor data quality, implement solutions, and communicate findings to Data and Solution owners, Management, and Stakeholders. Drives remediation of findings with stakeholders
Identify and implement methods of enforcing data quality at the point of entry