Data Engineer, Specialist
Role details
Job location
Tech stack
Job description
Vanguard's IT Data & Analytics team is seeking a Senior Data Engineer to design, build, and scale reliable data pipelines and reusable datasets that power IT reporting, dashboards, analytics products, and AI-ready data. In this role, you will partner with engineers, analysts, and technology stakeholders to ingest, transform, validate, and publish high-value data while improving usability and reducing manual effort. You will contribute to modern data engineering practices and help elevate data quality, governance, and accessibility across the organization. This is an opportunity to influence how data products are built and consumed across IT. This Hybrid Role (in office Tues-Wed-Thurs) is based in Charlotte, NC, Dallas, TX, Scottsdale, AZ, or Malvern, PA (HQ), * Design, build, and maintain scalable ETL/ELT pipelines for critical IT data sources
- Develop curated, high-quality datasets to support reporting, dashboards, and analytics products
- Write, optimize, and maintain SQL and Python code for transformation, automation, and performance
- Deliver cloud-based data solutions using AWS services such as Glue, S3, and Athena
- Partner with analysts, product managers, and stakeholders to translate data needs into practical solutions
- Implement data quality checks, validation rules, monitoring, and documentation to ensure trusted data
- Troubleshoot pipeline issues, investigate anomalies, and resolve data defects end-to-end
- Apply engineering best practices including version control (Git), code reviews, testing, and CI/CD deployment
- Contribute to standards for data lineage, governance, documentation, and production support
- Support the evolution of reusable data products and self-service analytics capabilities
Requirements
- Bachelor's degree or equivalent combination of education and relevant experience
- 3-5+ years of experience in data engineering, analytics engineering, or data platform development
- Strong proficiency in SQL and Python for data transformation and automation
- Hands-on experience building and supporting ETL/ELT pipelines
- Experience with AWS or similar cloud data platforms
- Solid understanding of data modeling, curated datasets, and BI/reporting use cases
- Demonstrated problem-solving skills and commitment to data quality and reliability
- Ability to communicate effectively with both technical and non-technical stakeholders
- Experience working in collaborative, agile team environments
Preferred:
- Experience with AWS Glue, PySpark, Athena, Dremio, Parquet
- Exposure to BI and visualization tools such as Tableau, Power BI, or Streamlit
- Familiarity with Jira, GitHub, ServiceNow, or technology operations data
- Interest in building reusable data products and enabling self-service analytics
- Exposure to AI/ML concepts, LLMs, or agent-based tools to enhance data engineering workflows and automation