Data Analyst- NBFI Data Standardization

leading-edge; Riyadh; On-site; SAR 100,000 - 150,000; Full time

Job summary

leading-edge is seeking a Data Analyst in Riyadh to standardize NBFI data. You will transform raw, unstandardized datasets into clean, actionable data assets, focusing on data cleaning, structuring, and validation.

You will build simple transformation pipelines using SQL and Python (Pandas), ingest large unstructured files, and collaborate with stakeholders to clarify data inconsistencies and support analytical reporting.

Qualifications

• SQL mastery with complex queries, joins, and aggregations.
• Python (Pandas) for data wrangling.
• Experience with messy, real-world datasets.
• Attention to detail in data cleaning and validation.
• Basic understanding of financial datasets.
• Excellent communication with stakeholders.

Responsibilities

• Ingest large, unstructured datasets from multiple NBFI sources (Excel, CSV, APIs, DBs).
• Clean & standardize data formats, schemas, and definitions across datasets.
• Build simple, scalable transformation pipelines using SQL + Python (Pandas).
• Create clean, analysis-ready datasets + basic reporting views for stakeholders.
• Document data definitions, assumptions, and lineage for auditability.
• Collaborate with NBFI teams to clarify data inconsistencies and validate outputs.

Skills

Attention to detail

Communication

Data wrangling

Tools

SQL

Python (Pandas)

Job description

Job Title: Data Analyst - NBFI Data Standardization

Location: Riyadh, Saudi Arabia

Job Type: Full-time

Job Summary

Our client is seeking a detail-oriented Data Analyst-NBFI Data Standardization to join their team in Riyadh and help transform raw, inconsistent datasets from multiple Non-Banking Financial Institutions (NBFIs) into clean, standardized, and actionable datasets. This role focuses on hands-on data cleaning, structuring, and validation

Key Responsibilities

• Ingest large, unstructured datasets from multiple NBFI sources (Excel, CSV, APIs, DBs)
• Clean & standardize data formats, schemas, and definitions across datasets
• Build simple, scalable transformation pipelines using *SQL + Python (Pandas)*
• Create clean, analysis-ready datasets + basic reporting views for stakeholders
• Document data definitions, assumptions, and lineage for auditability
• Collaborate with NBFI teams to clarify data inconsistencies and validate outputs

Must-Haves

• SQL mastery (complex queries, joins, aggregations)
• Python (Pandas) for data wrangling
• Experience working with *messy, real-world datasets*
• Attention to detail in data cleaning and validation
• Basic understanding of *financial datasets* (lending, portfolios, risk metrics)
• Communication skills to work with technical + non-technical stakeholders