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# Data Engineer, Specialist

- **Company:** Vanguard
- **Location:** Dallas, TX, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, JIRA, Cloud Database, Code Review, Continuous Integration, Data Validation, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Visualization, Github, Python (Programming Language), Machine Learning, Power BI, Cloud Services, SQL Databases, Tableau (Software), Parquet, Large Language Models, Git, Pyspark, Data Lineage, Streamlit Framework, Software Version Control, Data Pipelines, Servicenow
- **Published:** July 16, 2026
- **Apply:** https://www.juju.com/job/00000000gh0pwl

## About the Role

+ 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

## Description

+ 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


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