Data Analyst - Python/ETL (5-10 yrs)

Key Duties & Responsibilities :

- Reviews, develops and documents detailed data analytic routines, scripts, queries, and procedures that identify potential internal controls issues and recommends solutions.

- Emphasis on analytics delivery and quality, responsible for partnering across IAS and Company to brainstorm, define, design and implement analytics and supporting procedures across projects and critical business areas.

- Manages less complex audit engagements and teams in special projects or implementation of initiatives.

- Contributes to the development of analysis and automation solutions which shape the scoping of complex audits and related reviews.

- Researches and resolves difficult transactional issues.

- Experience in data acquisition (i.e. ETL, ELT), data management (cataloging, ensure quality, profiling), data analysis, Business Intelligence and advanced analytics (AI/ML/RPA)

- Employs multiple analysis and automation tools (e.g. Python, Snowflake, SQL, SSIS, Tableau, Power BI, RPA tools such as Selenium, Power Automate , DataStage, and APIs) and audit methods, techniques and approaches for obtaining optimal results.

- Liaises with senior management when communicating data analytic results and associated control recommendations.

- Advises senior personnel within Internal Audit and across the company resolve issues, gain needed information and influence outcomes.

- Manages performance of team through regular, timely feedback as well as the formal performance review process to ensure delivery of exceptional products and engagement, motivation, and development of team.

Required Experience :

- 4 years of experience in data analytics, statistical analysis, systems analysis, data warehousing and/or audit.

- Experience of data analytics in an audit environment, including experience in the management and/or use of data analytics tools and platforms such as SQL, Python, Tableau, Power BI, Selinium/Power Automate, Snowflake, and Splunk.

- 5 years of experience in data analytics, statistical analysis, BI & reporting, advanced analytics & automation, systems analysis, data warehousing and/or audit.

- Knowledge of financial services products, services and regulations.