Data Analyst

We are looking for a highly analytical Data Analyst with strong expertise in SQL, campaign management/campaign analytics, and banking (loans, mortgages, and deposits). The ideal candidate will work closely with business, marketing, and analytics teams to generate insights, optimise campaigns, and support strategic decision-making using data.
Responsibilities:
Analyse large datasets using SQL to generate actionable business insights.
Design, execute, and evaluate marketing/customer campaigns.
Measure campaign performance and recommend optimisation strategies.
Develop dashboards, reports, and KPIs for business stakeholders.
Perform customer segmentation, campaign targeting, and performance analysis.
Work with cross-functional teams, including Business, Marketing, Product, and Data Engineering.
Identify trends, opportunities, and risks using analytical techniques.
Ensure data quality, accuracy, and governance across reporting.
Support business decisions related to customer acquisition, retention, and cross-sell initiatives.
Present analytical findings to senior stakeholders in a clear and concise manner.
Requirements:
5-8 years of experience as a data analyst or campaign analyst.
Hands-on experience working with banking datasets.
Experience in campaign performance analysis and customer segmentation.
Strong understanding of banking products such as loans, mortgages, and deposits.
Experience working with large datasets and translating business problems into analytical solutions.
Mandatory Skills: SQL (Advanced), Campaign Management / Campaign Analytics, Banking Domain, Loans / Mortgages / Deposits, Data Analysis, and Stakeholder Management.
Technical Skills:
Strong SQL (Advanced Queries, Joins, CTEs, Window Functions, Performance Optimisation).
Experience in data analysis and reporting, campaign analytics / campaign management, and Excel (advanced).
Experience with BI tools such as Power BI, Tableau, or Looker (preferred).
Domain Expertise: Banking and Financial Services, Loans, Mortgages, and Deposits.
Preferred Qualifications:
Bachelor's degree in engineering, computer science, statistics, mathematics, economics, or a related quantitative field.
Experience with Python or R is an added advantage.
Knowledge of statistical analysis and A/B testing is preferred.
Exposure to cloud platforms (AWS, Azure, or GCP) is a plus.
Key Competencies:
Strong analytical and problem-solving skills.
Excellent stakeholder management.
Business acumen in retail banking.
Effective communication and presentation skills.
Ability to work in a fast-paced environment.
Attention to detail and ownership mindset.

Experience
5-8 yrs