Required Skills

Data Warehouse Analyst

Work Authorization

  • US Citizen

  • Green Card

  • EAD (OPT/CPT/GC/H4)

  • H1B Work Permit

Preferred Employment

  • Corp-Corp

  • W2-Permanent

  • W2-Contract

  • Contract to Hire

Employment Type

  • Consulting/Contract

education qualification

  • UG :- - Not Required

  • PG :- - Not Required

Other Information

  • No of position :- ( 1 )

  • Post :- 20th Feb 2024

JOB DETAIL

•    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.

Company Information