Data Engineering Lead: Scalable Pipelines & Cloud

Stanford University; Redwood City (CA); On-site; USD 138,000 - 164,000; Full time

Benefits offered by this job

Career development programs

Tuition-related support

Retirement plans

Family care resources

Health care benefits

On-site dining options

Free commuter programs

Employee discounts

On-site amenities

Fitness facilities and outdoor pool

Job summary

Stanford University in Redwood City, CA seeks an experienced data engineer to design, implement, and optimize complex data systems. You will build scalable pipelines, manage data lakes and warehousing, and document configurations across cloud and hybrid environments.

The role emphasizes mentoring, collaboration with stakeholders, and translating complex requirements into high-performing software. On-site work supports strong career development and campus resources.

Qualifications

• Bachelor's degree and five years of relevant experience, or equivalent combination
• Expertise in designing, developing, testing and deploying applications.
• Ability to define and solve logical problems for highly technical applications.
• Hands-on experience with Advanced SQL, Advanced Python, AWS services (S3, Redshift, Glue ETL, IAM, DMS, Appflow, VPC and others), Snowflake, FiveTran, Kafka, Airflow, Oracle Cloud and other open source tools
• Experience writing reusable complex Python/PySpark scripts for ELT, business logic or APIs; Scala or R a plus
• Hands-on development across data analysis, provisioning, modeling, performance tuning and optimization
• Experience working in AWS cloud environments and selecting tools that meet business requirements
• Ability to build scalable real-time and batch data pipelines using best practices in data modeling and ETL/ELT processing
• Proven experience in data modeling, data migration and data integration, including cross-SaaS integration challenges
• Strong communication skills with both technical and non-technical stakeholders

Responsibilities

• Independently design, implement and develop solutions for complex systems and programs
• Build applications involving sophisticated data manipulation and maintain data stores, data lakes, lake houses, and data warehousing solutions that are scalable, optimized, and fault-tolerant
• Document system builds and configurations, and keep documentation up to date
• Provide technical analysis, design, development, conversion and implementation workLead projects of moderate complexity as needed
• Serve as a technical resource for all data engineering applications
• Evaluate and integrate new features and technologies into the computing environment
• Adhere to the team software development methodology
• Mentor lower-level software developers
• Design and implement data migration and data integration across cloud and hybrid environments
• Demonstrate mastery of data engineering technologies and scripting languages
• Translate complex functional and technical requirements into detailed architecture and high-performing software
• Design, build and optimize data collection pipelines for storage, access and analytics

Skills

Advanced SQL

Advanced Python

Data pipeline design

Communication

Mentoring

Education

Bachelor's degree

Tools

AWS

Redshift

Snowflake

Airflow

Kafka

PySpark

SQL

Oracle Cloud

Job description

Stanford University in Redwood City, CA seeks an experienced data engineer to design, implement, and optimize complex data systems. You will build scalable pipelines, manage data lakes and warehousing, and document configurations across cloud and hybrid environments.

The role emphasizes mentoring, collaboration with stakeholders, and translating complex requirements into high-performing software. On-site work supports strong career development and campus resources.