Data Engineer

Saur Energy International; West Virginia; On-site; USD 65,000 - 90,000; Full time

Job summary

Saur Energy International is seeking an enthusiastic entry-level Data Engineer with a growing DevOps mindset to help build and maintain reliable, scalable data pipelines powering enterprise functions.

This is a great opportunity for an early-career engineer to learn, grow, and build hands‑on expertise — you'll support the team in developing data pipelines, learn CI/CD and operational practices, and take on increasing responsibility under the guidance of senior engineers.

Qualifications

• Bachelor's or Master's degree in Computer Science, IT, or related field.
• 1+ years of data engineering or related experience; internships count.
• Foundational knowledge of Databricks, Python (PySpark), and SQL.
• Experience building ETL/ELT data pipelines.
• Basic understanding of CI/CD pipelines and Git.
• Willingness to learn cloud platforms (AWS preferred).
• Good communication and eagerness to learn.

Responsibilities

• Help build and maintain data pipelines on Databricks under guidance.
• Develop ETL/ELT processes focusing on data quality, consistency, and scalability.
• Contribute to reusable data ingestion, transformation, and reconciliation frameworks.
• Follow coding standards and ETL/ELT best practices.
• Assist with deploying changes through CI/CD and CR lifecycle.
• Monitor data workloads and support incident response with guidance.
• Collaborate with Reporting, Platform, and Business teams; document workflows.

Skills

Databricks

Python

PySpark

SQL

Data Pipelines

CI/CD

Education

Bachelor's or Master's in CS/IT or related

Tools

Databricks

Job description

Position Summary

We are looking for an enthusiastic entry-level Data Engineer with a growing DevOps mindset to help build and maintain reliable, scalable data pipelines that power business functions across the enterprise. This is a great opportunity for an early-career engineer to learn, grow, and build hands‑on expertise — you'll support the team in developing data pipelines, learn CI/CD and operational practices, and take on increasing responsibility under the guidance of senior engineers.

Position Summary

We are looking for an enthusiastic entry-level Data Engineer with a growing DevOps mindset to help build and maintain reliable, scalable data pipelines that power business functions across the enterprise. This is a great opportunity for an early-career engineer to learn, grow, and build hands‑on expertise — you'll support the team in developing data pipelines, learn CI/CD and operational practices, and take on increasing responsibility under the guidance of senior engineers.

Core Skills

Databricks

• Python (PySpark)
• SQL
• Data Pipelines
• CI/CD

Key Responsibilities

Engineering & Delivery

• Help build and maintain data pipelines on Databricks under guidance.
• Develop ETL/ELT processes with attention to data quality, consistency, and scalability.
• Contribute to reusable frameworks for ingestion, transformation, and reconciliation across source systems.
• Follow established engineering standards — coding standards, pipeline patterns, and ETL/ELT best practices.

Operations & DevOps

• Assist with deploying changes through CI/CD and the Change Request (CR) lifecycle, including validation and ticket closure.
• Participate in problem‑solving and root‑cause analysis, learning to drive permanent fixes over recurring firefighting.
• Help monitor data workloads and support incident response with guidance from senior engineers.

Collaboration

• Work with Reporting, Platform, and Business teams to help deliver curated datasets for downstream consumers.
• Communicate progress and issues clearly to engineering peers and mentors.
• Document workflows and runbooks to support reproducibility and knowledge sharing.

What Success Looks Like (First 6–12 Months)

• In your first 6–12 months, you'll build a solid understanding of the data platform, confidently deliver assigned pipeline tasks, and become comfortable with CI/CD and operational practices — with support from senior engineers.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
• 1+ years of experience (including internships) in data engineering or a related area — fresh graduates with relevant internships are encouraged to apply.
• Foundational hands‑on knowledge of Databricks, Python (PySpark), and SQL for data processing.
• Exposure to building data pipelines (ETL/ELT), through projects, internships, or coursework.
• Basic understanding of CI/CD pipelines and Git‑based version control.
• Familiarity with cloud platforms (AWS preferred) or willingness to learn.
• Awareness of monitoring and observability concepts.
• Good communication skills and eagerness to learn.

Preferred Qualifications

• Exposure to orchestration frameworks or streaming technologies.
• Basic familiarity with Infrastructure‑as‑Code and deployment tooling.
• Awareness of observability tooling for data platforms.
• Background or interest in semiconductor manufacturing or large‑scale industrial data processing.
• Any Databricks or cloud certification is a plus.

Competencies

• Eagerness to learn and grow data engineering skills.
• Ownership mindset — takes pride in the quality of assigned work.
• Problem‑solving orientation — curiosity and attention to detail.
• Collaboration — works well with peers and mentors across teams.
• Clear communication — able to explain technical details to peers.