Data Engineer

TheCorporate LLC; Oakland (CA); Presencial; USD 130.000 - 180.000; Jornada completa

Descripción de la vacante

TheCorporate LLC is seeking a Data Engineer III in Oakland, CA to design, develop, and maintain scalable data pipelines and analytical solutions. You will build data products, dashboards, and applications in collaboration with architects, analysts and scientists to deliver actionable insights for utility and sustainability initiatives.

The ideal candidate brings 5+ years of data engineering experience, proficiency in Python, PySpark and SQL, and hands-on Palantir Foundry expertise.

Formación

• Bachelor’s degree in CS, Engineering, or related field.
• 5+ years as a Data Engineer.
• End-to-end data pipeline development (ingestion - delivery).
• Experience building reports, dashboards, and analytical applications.
• Advanced SQL and experience with large-scale datasets.
• Proficiency in Python and PySpark.
• Hands-on experience with Palantir Foundry (Workshop, Quiver, Contour, Slate).
• Familiarity with Tableau or Power BI.

Responsabilidades

• Collaborate with SMEs to design and implement data models, pipelines, and front-end applications.
• Transform raw data into clean, usable datasets and ontology objects for business applications.
• Monitor, troubleshoot, and resolve data quality issues and pipeline failures.
• Optimize pipeline performance (latency, cost, resource usage).
• Build operational apps using Palantir Foundry (Workshop, Quiver, Slate).
• Create interactive visualizations using Quiver and Contour.
• Evolve applications as business needs grow.
• Provide 24/7 operational support when needed.
• Mentor junior engineers and contribute to team best practices.

Conocimientos

Python programming

SQL querying

Data modeling

Problem solving

Mentoring

Educación

Bachelor’s in CS/Engineering or related field

Herramientas

Palantir Foundry

Workshop

Quiver

Contour

Slate

Tableau

Power BI

PySpark

Python

SQL

Descripción del empleo

Job Description: Data Engineer III

Job ID: PCGJP00005318

Location: Oakland, CA

Duration: November 16, 2026 — May 31, 2027

Work Arrangement: To be confirmed

Position Overview

The Data Analytics and Insights team is seeking an experienced Data Engineer to design, develop, and maintain scalable data pipelines and analytical solutions.

Key contributions include building data products, dashboards, and applications—while partnering with architects, analysts, and scientists to deliver high-impact insights for utility and sustainability initiatives.

Key Responsibilities

• Collaborate with SMEs to design and implement data models, pipelines, and front-end applications
• Transform raw data into clean, usable datasets and ontology objects for business applications
• Monitor, troubleshoot, and resolve data quality issues and pipeline failures
• Optimize pipeline performance (latency, cost, resource usage)
• Build operational apps using Palantir Foundry (Workshop, Quiver, Slate)
• Create interactive visualizations using Quiver and Contour
• Evolve applications as business needs grow
• Provide 24/7 operational support when needed
• Mentor junior engineers and contribute to team best practices

Minimum Qualifications

• Bachelor’s in CS, Engineering, or related field
• 5+ years as a Data Engineer
• End-to-end data pipeline development (ingestion - delivery)
• Experience building reports, dashboards, and analytical applications
• Advanced SQL and experience with large-scale datasets
• Proficiency in Python and PySpark
• Strong problem-solving and attention to detail
• Hands-on experience with Palantir Foundry (Workshop, Quiver, Contour, Slate)
• Familiarity with Tableau or Power BI

Required Technical Skills

Core Technologies Python, PySpark, SQL Data Engineering Data ingestion, pipelines, transformations, modeling, quality Data Platform Palantir Foundry Foundry Tools Workshop, Quiver, Contour, Slate Visualization Tableau, Power BI

Ideal Candidate Profile

A proactive, detail-oriented engineer with proven experience in Python, PySpark, SQL, and Palantir Foundry—comfortable owning end-to-end data solutions, resolving complex data issues, and collaborating across technical teams.