Education:
- Bachelor’s Degree in Computer Science, Information Systems, or other related field. Or equivalent work experience.
Experience:
- A minimum of 5 years of IT work experience in business intelligence tools and systems.
- Must have an extensive knowledge of data warehouse and data mart concepts.
- Must possess a working knowledge of Relational Database Management Systems (RDBMS) and data warehouse front-end tools.
Requirements/Responsibilities:
- Maintenance, upkeep, and redevelopment of an existing MS-SQL-based Data Warehouse, associated infrastructure, and processes.
- Document current infrastructure and processes.
- Analysis and strategic planning for data infrastructure services.
- Design the next iteration of data infrastructure.
- Uses data mining and data analysis tools.
- Reviews and validates data loaded into the data warehouse for accuracy. Interacts with user community to produce reporting requirements.
- Provides technical consulting to users of the various data warehouses and advises users on conflicts and inappropriate data usage.
- Responsible for prototyping solutions, preparing test scripts, and conducting tests and for data replication, extraction, loading, cleansing, and data modeling for data warehouses.
- Maintains knowledge of software tools, languages, scripts, and shells that effectively support the data warehouse environment in different operating system environments.
**Our client is searching for someone with 5+ years of experience for the following projects/tasks:
Develop BI Capabilities:
- Provide Dashboards, Scorecards, and Interactive Analytical reports.
- Train staff on all pertinent BI data structures and BI production
Design and implement Data Warehouse Architecture and Data Flow:
- Ingest Incremental Data into ODS from Source Systems.
- Apply Data Quality Assurance and business rules to transform the data.
- Store the transformed data in a Normalized Data Warehouse.
- From the Normalized Data Warehouse, build a Data Warehouse for Analytics.
- Build Data Marts per the business Analytics need.
- BI and data delivery layers – present different tools and methods to serve Analytics and reporting needs.
Project Management
- Set up DevOps for version control and Project Management.
- Fully incorporate the enterprise data management strategy into the solution.
- Thoroughly document Data Warehouse architecture to convey the objectives effectively.
Data discovery
- Identify data sources from business and responsible subject matter experts (SMEs).
- Analyze, develop, and document business process knowledge.
- Identify data quality issues at the source and challenges to resolving these issues.
- Identify and understand the relationship between different source systems.
Implement Dataedo software:
- Develop ERDs
- Work with SMEs to implement the Dataedo Data Dictionary
- Reporting critical reports and data required by the enterprise.
- Order of priority to help set the priority of deliverables.
- Current inventory of reports to identify what is currently in use.
Development
- Build Enterprise Data Warehouse.
- Data Warehouse Environment Build.
- Identify the Subject Area and data sources to start developing processes to build the Data Warehouse.
- Revise applicable data processes per discovery.