Data Analyst(Banking Domain)

Overview

Data Analyst drives high‑impact decisions by transforming complex financial and customer data into clear, actionable insights. They uncover patterns related to risk,fraud, profitability, and customer behavior, directly influencing lending, compliance, and growth strategies.

Key Responsibilities:

• Analyse and transform large datasets using PySpark and SQL to solve complex business problems.
• Identify data anomalies and perform thorough data validation to ensure accuracy and quality.
• Collaborate effectively with stakeholders, managing expectations and delivering data-driven solutions.
• Take ownership of the end-to-end data development and deployment process.
• Uphold data governance, quality, privacy, and control standards throughout the data lifecycle.

Technical Skills & Experience:
•  Minimum 5 years of professional experience in Python programming.
•  5-7 years of hands-on experience with PySpark for data management and transformation.
•  3-5 years of experience with SQL, including advanced query writing and optimization.
•  Familiarity with version control tools such as Git.
•  Strong understanding of data governance, data quality, controls, and privacy practices.

Preferred Skills:
•  Experience in the banking or financial services domain.
•  Knowledge of data pipeline building and workflow orchestration (e.g., Prophecy).
•  Ability to model data and design scalable data architectures.
•  Proven stakeholder management and communication skills.

Note: Data Engineers will not be considered for this role.