Role & Responsibilities
- Analyse large datasets related to payment processing, card issuance, and customer transactions to identify trends, patterns, and insights.
- Use statistical techniques and data mining tools to interpret data and generate actionable insights.
- Develop and maintain dashboards and reports to visualize data and track key performance indicators (KPIs).
- Work closely with business units, product managers, and other teams to understand data requirements and business objectives.
- Provide analytical support to stakeholders by delivering data-driven recommendations and insights.
- Communicate findings and insights effectively through presentations, reports, and visualizations.
- Develop, maintain, and optimize data pipelines with a focus on using dbt for data transformations, ensuring clean, reliable, and accessible data for analysis.
- Ensure the accuracy, completeness, and consistency of data used for analysis.
- Work with data engineers to implement data validation and cleansing processes to maintain high data quality.
- Create and maintain scalable data models in Snowflake using dbt, following best practices in chosen modelling technique.
- Identify opportunities for process improvements and optimization within payment processing and card issuance operations.
- Analyse operational workflows to recommend efficiency improvements.
- Monitor system performance and data trends to proactively address potential issues.
- Potentially contribute in ETL processes using dbt and orchestration tools (e.g., Apache Airflow), optimizing data workflows and performance.
- Ensure data analysis practices comply with industry standards, regulatory requirements, and security protocols.
- Assist in preparing data and reports for regulatory audits and compliance reviews.
- Proactively identify opportunities for process improvements and implement innovative solutions.
Preferred Candidate Profile
- Proven experience as a Data Analyst/Analytics Engineer role
- Proficiency in building and managing data transformations with dbt, with experience in optimizing complex transformations and documentation.
- Hands-on experience with Snowflake as a primary data warehouse, including knowledge of performance optimization, data modeling, and query tuning.
- Strong proficiency in data analysis tools and languages (e.g., SQL, Python).
- Strong understanding of data modeling principles and experience applying modeling techniques.
- Proficiencywith data visualization tools such as Tableau, Power BI, or similar.
- Knowledge of payment processing system, card issuance, and related services.
- Experience with cloud-based data solutions (e.g., AWS, Azure, Google Cloud).
- Familiarity with modern data architecture such as data Lakehouse.
- Strong analytical, problem-solving, and communication skills.
- Attention to detail and a commitment to data quality and integrity.
- Familiarity with regulatory requirements and security standards in the financial industry.
Skills: data analysis,modeling,transformations
