Data Engineer

Stellent IT LLC; United States; Remote; USD 110,000 - 150,000; Full time

Job summary

Stellent IT LLC is seeking an experienced Data Engineer to design, build, and optimize scalable data pipelines and analytics solutions within a large enterprise data ecosystem. The role requires strong SQL, Python, and BI skills, and will involve collaboration with stakeholders, engineers, analysts, and product teams.

Remote position open to USC or GC candidates, with potential conversion to full-time. The ideal candidate will have extensive experience in Google's ecosystem, Looker Studio

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Data Analytics, or a related technical field, or equivalent professional experience.
• 4+ years of hands-on experience as a Data Engineer, Analytics Engineer, or Data Analyst.
• Experience working within Google's ecosystem.
• SQL (PLX for Analytics): Experience writing complex, performance-tuned SQL queries, analytical functions, CTEs, and window functions to extract, transform, and model data across enterprise data warehouses.
• Python (- Colab/Jupyter): Experience with Python for scripting, data manipulation (Pandas/NumPy), basic ETL automation, and data validation.
• Looker Studio / PLX Dashboards: Experience designing interactive, self-service dashboards and business intelligence reporting.
• PLX Workflow: Experience with automated ETL/ELT scheduling and workflow orchestration within Google's data environment.
• Piper: Familiarity with Google internal distributed execution and data pipeline frameworks.
• Cider: Experience with Google internal code editing and cloud development tools. Responsible for source code management, writing and updating SQL/Python scripts, and engaging in collaborative code reviews.
• Linux: Understanding of command-line interfaces, directory navigation, file operations, shell scripting, and running automated cron jobs or background data processing tasks.

Responsibilities

• Responsible for building robust base tables, views, and data pipelines to support large-scale analytics.
• Expected to write, execute, and maintain automated scripts to process datasets, interact with APIs, and streamline data workflows.
• Responsible for connecting multi-source datasets, defining metrics/KPIs, optimizing load times, and delivering visual analytics to business stakeholders.
• Responsible for designing, scheduling, and monitoring robust data pipelines for scalable data ingestion, transformation, and distribution.
• Responsible for configuring, executing, and maintaining data processing pipelines to ensure seamless workflow integration and data pipeline reliability.

Skills

SQL

Python

Looker Studio

PLX Dashboards

PLX Workflow

Piper

Cider

Linux

Education

Bachelor's degree or equivalent experience

Tools

Google internal tools

Colab/Jupyter

Job description

Data Engineer

REMOTE

Must be USC or GC they might convert to full time

Seeking an experienced Data Engineer to design, build, and optimize scalable data pipelines and analytics solutions within a large enterprise data ecosystem. This role requires strong expertise in SQL, data engineering, workflow orchestration, and business intelligence, along with experience working in our Client s internal data platforms and environments.

The successful candidate will support large-scale data processing, analytics, reporting, and automation initiatives while partnering closely with business stakeholders, engineers, analysts, and product teams to deliver reliable and scalable data solutions.

Qualifications for success:

• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Data Analytics, or a related technical field, or equivalent professional experience.
• 4 or more years of hands-on experience as a Data Engineer, Analytics Engineer, or Data Analyst.
• Experience working within Google's ecosystem.
• SQL (PLX for Analytics): Experience writing complex, performance-tuned SQL queries, analytical functions, CTEs, and window functions to extract, transform, and model data across enterprise data warehouses.
• Python (- Colab/Jupyter): Experience with Python for scripting, data manipulation (Pandas/NumPy), basic ETL automation, and data validation.
• Looker Studio / PLX Dashboards: Experience designing interactive, self-service dashboards and business intelligence reporting.
• PLX Workflow: Experience with automated ETL/ELT scheduling and workflow orchestration within Google's data environment.
• Piper: Familiarity with Google internal distributed execution and data pipeline frameworks.
• Cider: Experience with Google internal code editing and cloud development tools. Responsible for source code management, writing and updating SQL/Python scripts, and engaging in collaborative code reviews.
• Linux: Understanding of command-line interfaces, directory navigation, file operations, shell scripting, and running automated cron jobs or background data processing tasks.

Key Responsibilities

• Responsible for building robust base tables, views, and data pipelines to support large-scale analytics.
• Expected to write, execute, and maintain automated scripts to process datasets, interact with APIs, and streamline data workflows.
• Responsible for connecting multi-source datasets, defining metrics/KPIs, optimizing load times, and delivering visual analytics to business stakeholders.
• Responsible for designing, scheduling, and monitoring robust data pipelines for scalable data ingestion, transformation, and distribution.
• Responsible for configuring, executing, and maintaining data processing pipelines to ensure seamless workflow integration and data pipeline reliability.