Position: Data Analyst/Business Analyst (2 Openings)
Location: SF Bay Area CA (onsite)
Duration: 612 Months
Significant Banking & Commercial Lending experience and share resume with the info what commercial lending product candidate have worked as DA/BA with SQL (2 Positions)
- US Banking ore banking platform FinacleRetail and Corporate lending Syndication loans Deposits etc. Must
- Commerical Lending Must Have
- Data Exploration Must
- Data Lineage Must
- Data Governance Must
- Data Quality Must
- Agile Must
- Tools used for Data Analysis SQL Must
- How did you showcase your findings Excel OK Anything else like Tableau or Power BI helps
- % of time spend in ETL < 20% overall.
- GAP analysis between as is and tobe process Must
- Databases SQL Server Oracle Teradata
- Crossfunctional teams to understand business requirements and contribute to designing data solutions that meet their needs Must
Job Description:
Mandatory: Data Analysis Experience in SQL Oracle/Teradata ETL technologies Experience working on SQL and ETL data warehouse applications.
- 7 years of experience on Business Data Analyst with an expertise in gathering Data requirements Data analysis Data profiling Data Mappings Data reconciliations and Data validations
- Experience in documenting business requirements and writing Business Requirement Document (BRD) Functional Requirement Documents (FRD) and Data Mappings Documents.
- Collaborating with crossfunctional teams to understand business requirements and contribute to designing data solutions that meet their needs.
- Experienced System/Data Analyst proficient in data wrangling data storytelling data visualization exploratory data analysis
- Expertise in GAP analysis between as is and tobe process
- Expertise in core banking platform FinacleRetail and Corporate lending Syndication loans Deposits etc.
- Extensive knowledge of data including investigation and analysis
- The ability to use SQL databases and good experience in ETL
- Collaborating with crossfunctional teams to understand business requirements and contribute to designing data solutions that meet their needs.