Data Engineer - On-Site in Sacramento, Build Data Pipelines

SBM

Sacramento, Northern (CA, KY)

Hybrid

USD 118,000 - 130,000

Full time

4 days ago
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Job summary

SBM is seeking a Data Engineer for the Sacramento office to design, evolve, and govern the data architecture supporting internally developed applications. This role will own the architecture of existing operational databases, develop scalable data models and pipelines, and guide data warehouse migration where appropriate.

The candidate will collaborate with the Integrations Engineer and other technology teams, building reliable batch and event-driven pipelines with SQL, PostgreSQL, and Python,

Qualifications

  • Bachelor’s degree in a technical field or equivalent experience.
  • 5+ years of data engineering and data architecture experience.
  • Strong SQL and Python development for data pipelines.

Responsibilities

  • Define and own the data architecture and implementation approach for internally developed application systems and BI solutions.
  • Design, build, test, document, and monitor reliable data pipelines using SQL, PostgreSQL, Python, and other approved platform technologies.
  • Partner with the Integrations Engineer to define data contracts and architectural boundaries between application databases and integration services.
  • Advise on database and data-modeling decisions and continually improve reporting processes.

Skills

SQL
Python
PostgreSQL
Data modeling
Data warehousing
ETL/ELT
AWS
SQL Server
Redshift

Education

Bachelor’s degree in a technical field

Tools

PostgreSQL
SQL Server
Amazon Redshift
AWS

Job description

SBM is seeking a Data Engineer for the Sacramento office to design, evolve, and govern the data architecture supporting internally developed applications. This role will own the architecture of existing operational databases, develop scalable data models and pipelines, and guide data warehouse migration where appropriate.

The candidate will collaborate with the Integrations Engineer and other technology teams, building reliable batch and event-driven pipelines with SQL, PostgreSQL, and Python,

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