Data Analyst-- NBFI Data Standardization

Leading Edge; Riyadh; On-site; SAR 120,000 - 180,000; Full time

Job summary

Leading Edge in Riyadh is seeking a detail-oriented Data Analyst - NBFI Data Standardization to transform raw, inconsistent datasets from multiple Non-Banking Financial Institutions into clean, standardized, and actionable datasets. This hands-on role focuses on data cleaning, structuring, and validation.

You will ingest large datasets from Excel, CSV, APIs and databases, standardize formats, and build simple, scalable transformation pipelines using SQL and Python (Pandas).

Qualifications

• Experience cleaning and standardizing large, messy datasets from multiple sources.
• Strong SQL expertise with complex queries and joins.
• Proficiency in Python (Pandas) for data wrangling.
• Attention to detail and ability to validate data.
• Ability to communicate with technical and non-technical stakeholders.

Responsibilities

• Ingest large, unstructured datasets from multiple NBFI sources (Excel, CSV, APIs, DBs).
• Clean and standardize data formats, schemas, and definitions across datasets.
• Build simple, scalable transformation pipelines using SQL and Python (Pandas).
• Create clean, analysis-ready datasets and 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

Data wrangling

Attention to detail

Communication

Tools

SQL

Python (Pandas)

Job description

Job Description:

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