Senior Data Steward

Walmart•Bentonville, AR

4d•$92,934 - $130,000•Onsite

About The Position

The Senior Data Steward will perform technical problem formulation, including analytics, big data analytics, and automation techniques. They will identify analytical methodologies to address business problems, conduct data source identification, and support the understanding of data requirements and service level agreements. This role involves performing initial data quality checks and implementing data governance practices in partnership with business stakeholders. The Senior Data Steward will also be responsible for data quality management, including profiling, analyzing, assessing, testing, validating, and continuously measuring data quality to meet service level agreements. They will promote data quality awareness and educate others on data governance processes and policies.

Requirements

Master’s degree in Analytics, Computer Science, or related field plus 1 year of experience in analytics or a related field; OR Bachelor’s degree in Analytics, Computer Science, or related field plus 3 years of experience in analytics or a related field.
Data extraction and querying in SQL
Collibra DGC/other Data Catalog tools
Data quality tools (Collibra CDQ, GooglePlex, SAP Master Data Governance)
Data quality profiling and issue remediation
MDM (Master Data Management) Repository
Creating dashboard using Tableau, Power BI, and Looker
Analytical data programming in Python and R
Data protection: data classification and data sharing policies and standards
Data certification process: framework, acceptance criteria, and operationalization
Data Modeling in ERWin/Microsoft SQL Server Management Studio
Maintaining data assets in Google Big Query/Data Discovery
Any amount of graduate coursework, graduate research experience or professional experience with the required skills.

Responsibilities

Performs technical problem formulation including analytics/big data analytics / automation techniques and methods; business understanding; precedence and use cases; business requirements and insights.
Identifies possible options to address the business problems within one's discipline through relevant analytical methodologies.
Conducts data source identification including functional business domain and scenarios; categories of data and where it is held; business data requirements; database technologies and distributed datastores (e.g. SQL, NoSQL); data quality; existing business systems and processes, including the key drivers and measures of success.
Supports the understanding of the priority order of requirements and service level agreements.
Identifies the most suitable source for data that is fit for purpose.
Performs initial data quality checks on extracted data.
Performs data governance including data value chains; data processes and practices; regulatory and ethical requirements around data; data modeling, storage, integration, and warehousing; data value chains (identification, ingestion, processing, storage, analysis, and utilization); data quality framework and metrics; regulatory and ethical requirements around data privacy, security, storage, retention, and documentation; business implications on data usage; data strategy; enterprise regulatory and ethical policies and strategies.
Establishes, modifies, and documents data governance projects and recommendations.
Implements data governance practices in partnership with business stakeholders and peers.
Interprets company and regulatory policies on data.
Educates others on data governance processes, practices, policies, and guidelines.
Provides recommendations on needed updates or inputs into data governance policies, practices, or guidelines.
Conducts data quality management including data quality management techniques and standards; business metadata definitions and content data definitions; data profiling tools, data cleansing tools, data integration tools, and issues and event management tools; understanding of user's data consumption, data needs and business implications; data modeling, storage, integration, and warehousing; data quality framework and metrics; user access best practices; enterprise data architecture, modeling and design, storage, integration, and warehousing; enterprise data quality framework and metrics; enterprise data strategy; enterprise data quality strategy; enterprise strategy to address regulatory and ethical requirements and policies around data privacy, security, storage, retention, and documentation.
Promotes and educates others on data quality awareness.
Profiles, analyzes, and assesses data quality.
Tests and validates data quality requirements.
Continuously measures and monitors data quality.
Delivers against data quality service level agreements.