Snowflake delivers the AI Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the AI Data Cloud, organizations unite their siloed data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds. Snowflake’s platform is the engine that powers and provides access to the AI Data Cloud, creating a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing. Join Snowflake customers, partners, and data providers already taking their businesses to new frontiers in the AI Data Cloud.

Snowflake is growing and looking for a driven Auditor to join our team. You will report to the Senior Manager, Internal Audit - Business and help with an evolving workload with minimal supervision in a fast-paced environment. Whether it is supporting Snowflake’s Enterprise Risk Management (ERM) program or conducting internal audits, we strive to enhance the effectiveness, efficiency and scalability of the company’s processes, systems, and underlying internal control environment. You will be expected to leverage data to generate powerful insights and solutions, problem solve, collaborate closely with stakeholders, and move fast while keeping attention to detail.

AS AN INTERNAL AUDIT DATA ANALYST YOU WILL:

Design, and develop data analytics to support operational audit activities, including building and automating audit tests, anomaly detection, audit scoping e.g. risk scoring, developing techniques for continuous monitoring, and generating insights, and visualizations including dashboards. You will leverage the Snowflake platform to build and maintain models that provide enhanced insight into risks and controls, establish an efficient/automated means to analyze and test large volumes of data for outliers, anomalies, patterns, and trends, and help evaluate the adequacy and effectiveness of process and controls.

Design, build, and execute data analytics for ERM (Enterprise Risk Management) initiatives, including developing analytics to monitor Key Risk Indicators (KRIs), identify emerging risk trends, and provide data-driven support for the ERM program and ERM risk assessments.

Interact with management and business partners to identify appropriate data sources and data elements required for analytics, validating the completeness and accuracy of data received.

Champion a data-first mindset within the team, research and communicate best practices, identify areas for improvement and opportunities to use data analytics and tools to improve our audit processes, and provide effective recommendations and sound audit conclusions. You will be empowered to challenge the status quo, develop new analytical approaches, and create tools that enhance the audit process.

Execute and support end-to-end operational audits over key business processes to identify areas of risk, evaluate the effectiveness of controls, and identify opportunities for process improvement.

Participate in risk assessments and the design of audit programs in order to address relevant risks.

OUR IDEAL INTERNAL AUDIT DATA ANALYST WILL HAVE:

Bachelor’s degree in Data Science, Computer Science, Business, Accounting or Finance.

Relevant work experience in internal audits, risk analysis, internal controls, fraud, compliance, data analysis, business intelligence, or controls assessment.

3+ years of relevant data analysis in audit, financial, risk management, or technology functions experience.

Experience in supporting the execution of SOX programs, control principles (e.g. COSO) and other internal audits, is a plus.

Experience with cloud-based or software as a service (SAAS) companies, and certifications like AWS, Azure and Google Cloud is strongly preferred.

Strong quantitative, analytical, data-intuition, and problem-solving skills, and proficiency in data analytics techniques and query/programming languages in SQL and Python, for data analysis and machine learning.

Hands-on experience working with data visualization tools.

Experience with Big 4 accounting firms or global public companies and consulting is a plus.

A strong sense of analytical curiosity and the ability to ask probing questions to understand complex business processes and data context.

Detail and team orientated; ability to work both independently and as a team member.

Self-starter, ability to proactively problem-solve, identify, advocate for and execute improvements.

Ability to manage multiple, concurrent projects efficiently and effectively with minimal oversight. Maintain relationships with process owners and other key stakeholders.