Role: Data Analyst (Python & SQL) Senior
Location: Must onsite in Los Angeles CA or Orange County CA 23 days a week
Topics in the interview ( recent interviews) :
- SQL Intermediate to complex query writing
- Python
- Data warehousing
- Data Modelling
Python should have the practical knowledge working experience ( not just theoretical knowledge).
SQL should be strong in advanced SQLs such as JOINs Rank and complex SQL scenarios.
Communication skills Client facing role Need 8/10
Look for the Candidates who worked with big consulting companies like Deloitte/ KPMG. ( They mostly have the experience in the client facing roles additional to the technical skills set ).
Top Skills:
Data Analytics
Investment Optional
Asset management Optional
Financial Industry is required Last candidate we placed from Vanguard Financial so
SQL
Python
68 years of experience in the Financial Services industry Asset management experience/Investment operations and data management experience preferred.
Top 3 skills
- Strong in advanced data analytics using Python and SQL
- Experienced in functional and nonfunctional data requirements such as mapping flows data dictionary glossary lineage operational metadata etc..
- Strong background and experience in capital markets/investment management domain
Job Description
- Asset Management and Investment Operations experience is preferred Financial Industry experience is Required
- Gather source and target data requirements identify and analyze datasets for data product suitability
- Conduct detailed data analysis on large data sets generating insights on data gaps trends and areas for improvement
- Develop points of view (POVs) through data analysis to support product feature decisions
- Assist Data Product Managers in defining and prioritizing features
- Create and maintain sourcetotarget mapping documents and productrelated documentation
- Develop and execute test scripts for Functional Testing and User Acceptance Testing (UAT) for data products
- Document data validation controls and collaborate with the engineering team to guide implementation
- Prepare data product release notes for operational readiness
- Participate in Program Increment (PI) planning daily standup sprint demo and sprint retrospective meetings fostering transparency feedback and continuous improvement.
- Must have excellent client communication and presentation skills