About this role
The Data Analyst is a developing professional role. Applies specialty area knowledge in monitoring, assessing, analyzing and/or evaluating processes and data. Identifies policy gaps and formulates policies. Interprets data and makes recommendations. Researches and interprets factual information. Identifies inconsistencies in data or results, defines business issues and formulates recommendations on policies, procedures or practices. Integrates established disciplinary knowledge within own specialty area with basic understanding of related industry practices. Good understanding of how the team interacts with others in accomplishing the objectives of the area. Develops working knowledge of industry practices and standards. Limited but direct impact on the business through the quality of the tasks/services provided. Impact of the job holder is restricted to own team.
Responsibility :
1. Data Analysis, Querying & Extraction
- Develop, optimize, and maintain complex SQL queries and SAS scripts/macros to extract, transform, and aggregate datasets from relational databases and enterprise data lakes.
- Conduct data analysis, data reconciliation, validation, and quality assessments across multifaceted financial and transactional datasets.
- Perform root cause analysis for data discrepancies and collaborate with upstream/downstream data owners to implement robust resolutions.
2. Reporting & Dashboard Development : Good to have
- Translate business requirements and ad-hoc analytics requests from stakeholders into clean, interpretable, and high-impact data deliverables.
- Streamline manual reporting cadences to tools like tableau.
4. AI Tool Adoption & Continuous Innovation
- Have an idea or exposure to leverage modern AI productivity tools and workflows (e.g., AI-assisted code generation, data exploration, automated documentation, process automation) to enhance operational efficiency
Requirement:
- Experience: Minimum 3+ years of hands-on professional experience in data analysis, reporting, and database programming.
- Core Technical Competencies: SAS: Intermediary to advance proficiency in Base SAS, SAS Macros, PROC SQL, and data step processing.
- SQL: Strong hands-on querying, complex joins, subqueries, analytical window functions, indexing, and query optimization across enterprise RDBMS +Basics of python /Spark and understanding of HIVE
- Good to have BI & Reporting Tools: Direct hands-on experience developing reports and visual dashboards in at least one enterprise reporting platform (e.g., Tableau, Power BI, Qlik, MicroStrategy, or SAP BusinessObjects).
- Domain Knowledge: understanding of banking, financial services operations, and core financial metrics.
- Analytical & Logical Capabilities: Good problem-solving, critical thinking, and structured analytical skills with keen attention to detail.
- Proven ability to dissect complex data logic and design elegant, maintainable analytical solutions.
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
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## Job Family Group:
Decision Management
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## Job Family:
Data/Information Management
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## Time Type:
Full time
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## Most Relevant Skills
Please see the requirements listed above.
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## Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
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