Boston University

Data Engineer III AI, Automation, & Data Engineering

Boston University Boston, Massachusetts, United States · $120K–$150K/yr

Higher Education · 51-200 employees

4 d ago
data-engineer Mid (2-5 yrs) Full-time United States
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About the role

Design and maintain scalable DAG-based data pipelines and infrastructure to support institutional research and analytics. Collaborate with cross-functional teams to optimize ETL workflows, ensure data quality, and implement robust data governance standards.

What they look for

Python SQL PostgreSQL Dagster AWS ETL Data modeling Kubernetes Docker CI/CD Git Data governance Data warehousing Streaming architectures Agile Communication

Requirements

Requires at least 3 years of experience in data engineering, backend development, and proficiency in Python and SQL. A degree in Computer Science or a related field is required, with a Master's degree preferred.

Benefits

Paid time off Paid intersession break 13 paid holidays University-funded retirement plan Tuition assistance program Wellness resources

Full description

Boston University Information Services & Technology (IS&T) is seeking applicants with diverse skills and experiences to join our innovative and inclusive community. Join us as a Data Engineer III, helping advance the university's data and analytics capabilities by designing and scaling modern data pipelines and platforms. Your work will directly support institutional reporting, research, and strategic initiatives. You will work on modern data infrastructure using tools, collaborate with data architects, analysts, and application developers to design robust ETL workflows, optimize performance, and ensure data quality and governance at scale. The Data Engineering team within IS&T plays a critical role in enabling data-driven decision-making across Boston University. We develop and maintain data infrastructure that supports analytics, institutional research, academic planning, and operational efficiency. Our team partners closely with data consumers across the university to ensure the reliability, scalability, and quality of enterprise data assets. You Will Design and maintain scalable DAG-based data pipelines using Dagster. Build and optimize data models in PostgreSQL using DBT for analytical and operational use cases. Develop batch and streaming ETL processes leveraging AWS services (S3, Glue, Athena, SNS/SQS, Lambda). Deploy and manage containerized workloads on Kubernetes, using infrastructure-as-code. Implement robust data quality checks, observability, and automated validation. Define schemas, data contracts, and transformation logic with cross-functional teams. Contribute to CI/CD workflows (e.g., GitHub Actions, ArgoCD) to perform code reviews and document technical standards.

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