Business Analyst / Data Analyst

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Stanley David and Associates, is seeking the following. Apply via Dice today!

Must Have Technical/Functional Skills:

Required Skills:

• Strong hands-on expertise in SQL (Mandatory) – complex queries, joins, aggregations, performance tuning.
• Experience in data analysis and data testing.
• Good understanding of ETL processes and data validation techniques.
• Strong analytical and problem-solving skills.
• Ability to interpret and validate business rules in data context.
• Strong communication and stakeholder interaction skills.
  
  

Domain Expertise:

• Mandatory experience in Banking and Financial Services.
  
  

Understanding of:

• Financial data models.
• Transaction processing systems
• Regulatory and reporting requirements
  
  

Preferred Skills:

• Exposure to Python or SAS (nice to have).
• Experience with data visualization/reporting tools (Power BI, Tableau, etc.).
• Familiarity with data warehousing concepts
  
  

Key Competencies:

• Strong analytical thinking.
• Attention to detail and data accuracy.
• Stakeholder communication.
• Problem-solving mindset.
• Ability to work in cross-functional teams
  
  

Roles & Responsibilities:

Key Responsibilities:

Business Analysis:

• Gather, analyze, and document business and functional requirements.
• Work closely with stakeholders to translate banking business needs into data requirements.
• Participate in requirement grooming, gap analysis, and solution design.
  
  

Data Analysis

• Perform in-depth analysis of large datasets using SQL.
• Generate insights and validate business rules through data exploration and profiling.
• Support reporting and decision-making with accurate data interpretation.
  
  

Data Testing

• Design and execute data validation and testing strategies.
• Perform data reconciliation between source and target systems.
• Validate data transformations, business logic, and ETL processes.
• Identify data issues and conduct root cause analysis to ensure resolution.
• Ensure data accuracy, completeness, and consistency across systems.