Data Engineer, Specialist

The Vanguard Group•Malvern, PA

1d•Hybrid

About The Position

The Data Engineer, Specialist designs, develops, and optimizes ETL processes, data pipelines, database solutions, and cloud-based data infrastructure to support scalable, reliable data processing and analytical needs. The role integrates large, complex datasets from multiple sources and troubleshoots data and software issues to maintain data consistency, quality, availability, and integrity. It translates business and regulatory requirements into technical designs and develops maintainable, reusable code, queries, and data solutions. The specialist builds AWS cloud-supporting services and technologies, including Glue, Redshift, Step Functions, Amazon Q foundational services such as IAM, CloudWatch, CloudFormation, Lambda, Secrets Manager, and SageMaker. The position also builds Spark data-processing applications, creates dashboards and visualizations using Power BI or similar platforms, and automates recurring analysis and reporting workflows with Python, SQL, and other programming tools. The role partners with business, compliance, analytics, technology, and leadership teams to understand data needs, communicate technical considerations, and translate findings into clear insights for technical and non-technical audiences. It assesses data quality, tests solutions for their intended purpose, supports production implementation using established engineering and release practices, and serves as a subject matter expert by mentoring less-experienced data professionals and contributing to engineering standards and reusable practices. The position also participates in special projects and performs other duties as assigned. It supports data and reporting capabilities associated with Financial Crimes and regulatory compliance. This is a hybrid role based in Malvern, Pennsylvania, with in-office work Tuesday through Thursday. Vanguard states that it is not offering visa sponsorship for this position.

Requirements

At least 8 years of experience in data engineering, programming, database development or administration, data management, or related data-focused disciplines.
Undergraduate degree or an equivalent combination of education, training, and relevant experience.
Experience developing and optimizing ETL processes, data pipelines, and solutions integrating data from multiple sources.
Experience using SQL for data querying, transformation, troubleshooting, and data-quality analysis.
Experience using Python or other programming languages to develop data solutions and automate workflows.
Experience developing reports, dashboards, or data visualizations using Power BI or similar platforms.
Experience translating business requirements into technical solutions and communicating with technical and non-technical stakeholders.

Nice To Haves

Experience with cloud-based data platforms or large-scale data-processing environments.
Experience supporting Financial Crimes, SEC regulatory reporting, regulatory compliance, or financial services data.

Responsibilities

Design, develop, and optimize ETL processes, data pipelines, database solutions, and cloud-based data infrastructure.
Integrate large and complex datasets from multiple sources and troubleshoot data and software issues to maintain data consistency, quality, availability, and integrity.
Translate business and regulatory requirements into technical designs and develop maintainable, reusable code, queries, and data solutions.
Build AWS cloud-supporting services and technologies, including Glue, Redshift, Step Functions, Amazon Q foundational services, IAM, CloudWatch, CloudFormation, Lambda, Secrets Manager, and SageMaker.
Build Spark data-processing applications.
Build and automate dashboards, reports, and data visualizations using Power BI or similar platforms.
Automate recurring data analysis and reporting workflows using Python, SQL, and other programming tools.
Partner with business, compliance, analytics, and technology teams to understand data needs, develop solutions, and communicate technical considerations.
Collaborate with leadership and business partners to explain data and analytical findings to technical and non-technical audiences.
Assess data quality, test solutions for their intended purpose, and support production implementation using established engineering and release practices.
Serve as a data engineering and analytics subject matter expert, mentor less-experienced data professionals, and contribute to engineering standards and reusable practices.
Participate in special projects and perform other duties as assigned.
Support data and reporting capabilities associated with Financial Crimes and regulatory compliance.