Data Engineer II: Scale BI Pipelines

Socket.dev; Dallas (TX); On-site; USD 139,000 - 179,000; Full time

Job summary

AMAZON.COM SERVICES LLC in Dallas, Texas, seeks a Data Engineer II to design, develop, and operate large-scale data structures for business intelligence analytics. You will implement data structures using data modeling, ETL/ELT processes, SQL, Oracle, and OLAP technologies, providing online reporting and analysis across multi-source datasets.

The role involves gathering requirements, translating them into scalable solutions, and guiding end-to-end data lifecycle, from design to maintenance,

Qualifications

• Master’s degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or related field and one year of experience, OR Bachelor’s degree with five years of progressive post-baccalaureate experience.
• Experience in developing and operating large-scale data structures for business intelligence analytics using ETL/ELT, OLAP, data modeling, SQL, and Oracle.

Responsibilities

• Design, develop, implement, test, document, and operate large-scale data structures for BI analytics.
• Implement data structures using data modeling, ETL/ELT, SQL, Oracle, and OLAP technologies.
• Provide online reporting and analysis using OBIEE and a multi-source data architecture.
• Gather requirements and translate them into robust, scalable solutions.
• Mentor junior data engineers.

Skills

ETL/ELT

OLAP

Data modeling

SQL

Oracle

Education

Master's degree or related field

Bachelor's degree + 5+ years experience

Job description

AMAZON.COM SERVICES LLC in Dallas, Texas, seeks a Data Engineer II to design, develop, and operate large-scale data structures for business intelligence analytics. You will implement data structures using data modeling, ETL/ELT processes, SQL, Oracle, and OLAP technologies, providing online reporting and analysis across multi-source datasets.

The role involves gathering requirements, translating them into scalable solutions, and guiding end-to-end data lifecycle, from design to maintenance,