Senior Data Analyst

Job Description:

Job Summary:

We are seeking an experienced Senior Data Analyst to drive data-driven decision-making across business functions. The ideal candidate should possess strong expertise in analytics, data engineering, automation, and stakeholder management. This role requires hands-on experience in building scalable ETL pipelines, analytical data models, automated reporting systems, and advanced analytics solutions. Will work closely with business, product, risk, operations, and leadership teams to deliver actionable insights, optimise processes, and support strategic initiatives.

Key Responsibilities:

• Design, develop, and maintain scalable ETL pipelines and automated data workflows using Python, SQL, PySpark, and MongoDB.
• Analyse large and complex datasets to generate actionable business insights and solve critical business problems.
• Build and optimise analytical data models, data marts, and reporting layers for business intelligence and decision-making.
• Develop and automate MIS reports, dashboards, and KPI frameworks using BI tools such as Power BI.
• Perform data validation, anomaly detection, and implement robust data quality checks across the data lifecycle.
• Collaborate with stakeholders across Risk, Collections, Underwriting, Marketing, and Operations teams to understand business requirements and translate them into scalable analytical solutions.
• Design and maintain data warehouse and data lake structures to support enterprise reporting and analytics.
• Drive end-to-end ownership of analytics projects from requirement gathering to deployment and monitoring.
• Optimise SQL queries and data processing workflows to improve performance and reduce execution time.
• Ensure adherence to data governance, privacy, security, and quality standards.
• Mentor junior analysts and contribute to building best practices within the analytics team.

Required Skills:

• 5+ years of hands-on experience in Python for data analysis, automation, and ETL development.
• Strong expertise in SQL with experience in query optimisation and performance tuning.
• 2+ years of hands-on experience with PySpark for large-scale data processing.
• Experience working with MongoDB and handling large datasets.
• Strong understanding of ETL processes, data warehousing, and data modelling.
• Experience with Power BI or similar BI and reporting tools.
• Strong analytical, problem-solving, and stakeholder management skills.
• Excellent communication skills with the ability to work across cross-functional teams.

Preferred Skills:

• Experience in financial services, lending, risk analytics, or fintech domains.
• Exposure to cloud platforms and modern data architectures.
• Knowledge of data governance, data quality frameworks, and automation best practices.