A Data Analyst develops computer programs to analyze large customer information databases for companies and organizations. Analyzes data to identify patterns and provide information relevant to a particular business, industry or field; analysis may be used for marketing, or to detect fraud in financial transactions, or for research. Develops computer programs to protect confidential customer information.
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Sr. Data Analytics Engineer - Internal Audit page is loaded
Sr. Data Analytics Engineer - Internal Audit
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locations
Malvern, PA
time type
Full time
posted on
Posted 6 Days Ago
time left to apply
End Date:
September 2, 2026 (15 days left to apply)
job requisition id
181430 Vanguard's Internal Audit & SOX (IAS) department has an exciting opportunity in our Automation and Analytics team. We're looking for a tech-savvy, innovative individual who's passionate about building scalable data solutions and engineering robust analytics infrastructure. This role is a crucial part of our forward-thinking, dynamic team and is key to delivering automated utilities and data pipelines that provide greater assurance to the organization, increase stakeholder productivity, and deliver deeper insights into the operating effectiveness of our control environment—all of which ultimately support Vanguard's purpose: to take a stand for all investors, to treat them fairly, and to give them the best chance for investment success. You'll collaborate with a diverse and talented team of centralized and decentralized data analysts, and work closely with our analytics infrastructure and solutions using the latest technologies. The ideal candidate will have a strong background in data engineering, technical communication, and automation development, with hands-on experience in System frontend development, Streamlit, cloud platforms, Python, and data pipeline design.
Responsibilities:
Data Engineering & Pipeline Development:
Design, build, and maintain scalable data pipelines and ETL processes to support analytics and automation initiatives. Ensure data quality, integrity, and performance across systems.
Requirements Gathering and Technical Design:
Partner with stakeholders to translate business needs into technical specifications. Design data models, process flows, and system integrations aligned with strategic objectives.
Automation Development:
Develop and deploy automation tools and scripts (e.g., Python, SQL, Power Apps) to streamline audit and business processes, improve efficiency, and reduce manual effort.
Data Visualization:
Support the development of reporting front-end interfaces using tools such as Streamlit, hosted on AWS infrastructure. Collaborate with analytics and audit teams to design user-friendly applications that deliver insights and enable interaction with automated utilities and data pipelines.
Infrastructure & Systems Integration:
Collaborate with IT and analytics teams to implement integrated solutions using cloud platforms (e.g., AWS), databases (e.g., SQL Server), and identity systems (e.g., Active Directory).
Process Optimization:
Identify and implement opportunities for process improvement through automation and data-driven insights within internal audit workflows.
Innovation & Technology Adoption:
Stay current with emerging technologies (e.g., Gen
AI, RPA, AI/ML
) and recommend innovative solutions that align with organizational strategies.
What It Takes:
Proficiency in Python, SQL, and data engineering tools and frameworks.
Experience with data visualization platforms (e.g., Tableau, Power BI), cloud infrastructure (e.g., AWS), and database systems (e.g., SQL Server).
Familiarity with RPA, AI/ML concepts, and modern data architecture.
Strong communication skills to bridge technical and non-technical stakeholders.
Ability to thrive in a fast-paced, ambiguous environment and manage multiple priorities.
Strong planning and organizational skills with a focus on execution and delivery.
Qualifications:
Minimum of 5 years related technical experience; some working knowledge of audit, risk, and controls.
Undergraduate degree in a related field or the equivalent combination of training and experience (e.g., MIS, Information Technology, Data Sciences, Data / Business Analytics).
