Determines database requirements by analyzing business operations, applications, and programming; reviewing business objectives; and evaluating current systems.
Obtains data model requirements, develops and implements data models for new projects, and maintains existing data models and data architectures.
Develops physical databases meeting performance requirements.
Develops strategies for database implementation.
Develops data structures for data warehouses and data mart projects and initiatives; and supports data analytics and business intelligence systems.
Implements corresponding database changes to support new and modified applications, and ensures new designs conform to data standards and guidelines; are consistent, normalized, and perform as required; and are secure from unauthorized access or update.
Defines and implements processes for extracting and loading data; identifies appropriate data sourcing and extraction processes, and in identifying and nominating sources as systems of record for data usage in various applications.
Provides guidelines on creating data models and various standards relating to governed data.
Reviews changes to technical and business metadata, realizing their impacts on enterprise applications, and ensures the impacts are communicated to appropriate parties.
Configures and establishes data catalog to inventory, classify, and map data throughout the enterprise.
Establishes measures to chart progress related to the completeness and quality of metadata for enterprise information; to support reduction of data redundancy and fragmentation and elimination of unnecessary movement of data; and to improve data quality.
Assists in selecting data management tools and developing the standards, usage guidelines, and procedures for using those tools.
Assists in performing root cause analyses related to information issues and non-conformance to published data standards based on review of technical metadata of various source systems.
May supervise the work of others.
May travel up to 5% of the time. Involves overnight travel. Travels by plane and/or car. May require working extended hours and some evenings and weekends, as needed.

Requirements

Graduation from an accredited four-year college or university with a degree in data science, data management, computer information systems, management information systems, computer science, cybersecurity or information security, or in a field related to assignment.
Five (5) years’ experience in enterprise data architecture and/or information architecture work, two (2) years of which were in a lead or supervisory capacity.
Five (5) years of experience in relational modeling and design (OLTP and OLAP).
Five (5) years of experience with full life cycle architecture, development, implementation, and management of operational databases and enterprise data warehouses.
Five (5) years of experience leading stakeholder engagements on the gathering, documentation & detailed analysis of business requirements.
Three (3) years of experience with DB2, SQL Server, and stored procedure development.
Three (3) years of experience building data pipelines and ETL solutions.
Three (3) years of experience with data engineering for business intelligence and business analytics.
Three (3) years of experience with ETL tools (Informatica PowerCenter, Informatica Cloud ETL, Azure Data Factory).

Benefits

Retirement Plan
Paid Group Health & Life Insurance for employees
Paid Holidays
Paid Vacation Leave
Paid Sick Leave
Longevity Pay
Dental
Vision
Dependent Optional Life Insurance
Voluntary AD&D Insurance
Dependent Health & Life Insurance
Health & Dependent care flexible spending accounts
Tuition Assistance Program

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data modelingdata architecturerelational modelingOLTPOLAPETL solutionsdata engineeringstored procedure developmentbusiness intelligencedata analytics

Soft Skills

leadershipstakeholder engagementcommunicationanalysisproblem-solving