Software Engineering Intern – Data Engineering (Cloud & Streaming)

Posted 9 Days Ago
Be an Early Applicant
Fremont, CA
In-Office
40-55 Hourly
Internship
Energy • Renewable Energy
The Role
Join the Data Engineering team to develop production data pipelines using Azure technologies, focusing on streaming ingestion and lakehouse architecture. Gain hands-on experience and mentorship while ensuring data reliability and performance.
Summary Generated by Built In

Job Description:

Nextpower is seeking a highly motivated summer intern to join the Data Engineering team to help build and operate production data pipelines that power analytics and operational insights from power plant telemetry. This role will report to a data engineering leader and will focus on developing reliable, cost-efficient streaming and lakehouse pipelines on Azure.

This internship offers direct, hands-on experience delivering real production data systems—working with streaming ingestion, Delta Lake lakehouse patterns (Bronze/Silver/Gold), and data quality engineering. Interns will work closely with experienced engineers and stakeholders, receive meaningful mentorship, and gain exposure to how data products are designed, delivered, and supported in production.

Key Responsibilities
  • Build and operate telemetry data pipelines from ingestion through curated lakehouse tables
  • Implement streaming ingestion using Kafka concepts (e.g., Azure Event Hubs or similar technologies)
  • Develop Databricks lakehouse pipelines producing Bronze/Silver/Gold Delta tables (or equivalent patterns)
  • Enforce schema validation, data contracts, and data quality checks (e.g., expectations/tests)
  • Handle real-world pipeline issues such as late-arriving data, duplicates, out-of-order events, and schema drift
  • Optimize pipelines for performance, reliability, and cost
  • Create clear documentation and runbooks to support owned pipelines in production
  • Collaborate with engineers and stakeholders to translate requirements into robust, maintainable data products
Qualifications
  • Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Engineering, Software Engineering, or a related field (or equivalent practical experience)
  • Proficiency in Python and/or SQL, with the ability to write clean, maintainable code
  • Strong understanding of data fundamentals (schemas, data modeling basics, transformations, and data reliability concepts)
  • Exposure to distributed systems and/or big data concepts (e.g., Spark, streaming, or parallel processing)
  • Strong analytical and troubleshooting skills; ability to debug issues using logs, metrics, and data inspection
  • Excellent written and verbal communication skills, including comfort documenting work clearly
  • Comfortable working in a fast-paced, high-performance environment with mentorship and feedback

Nice to Have (Not Required)

  • Experience with Azure (Event Hubs, ADLS Gen2) or cloud data platforms (AWS/GCP equivalents)
  • Experience with Databricks, Delta Lake, or lakehouse architectures
  • Exposure to streaming (Kafka or similar) and event-driven data pipelines
  • Familiarity with data quality practices (tests, validation, data contracts) and CI/CD
What You Will Gain
  • Hands-on experience building and supporting production-grade data pipelines for real telemetry systems
  • Practical exposure to Azure-based data platform architecture and streaming fundamentals
  • Experience implementing lakehouse design principles using Bronze/Silver/Gold patterns (or equivalent)
  • Real-world data reliability engineering skills: handling late data, duplicates, schema evolution, and correctness
  • Mentorship from experienced engineers and insight into how data engineering supports business and operational outcomes
  • Strong portfolio-worthy deliverables: production pipeline components, documentation, and measurable improvements

 

Important Note: We welcome applicants who do not match the exact tech stack. If you have strong fundamentals and have built data pipelines or backend systems in any modern stack (AWS/GCP/on-prem, Kafka/Kinesis/PubSub, Spark/Flink, etc.), we encourage you to apply—we will consider you equally.

Compensation

Pay is based on market location and may vary based on factors including experience, skills, education and other job-related reasons. The hourly pay range for this position is $40-55 per hour (specific to California).

 

At Nextpower, we are driving the global energy transition with an integrated clean energy technology platform that combines intelligent structural, electrical, and digital solutions for utility-scale power plants. Our comprehensive portfolio enables faster project delivery, higher performance, and greater reliability, helping our customers capture the full value of solar power. Our talented worldwide teams are redefining how solar power plants are designed, built, and operated every day with smart technology, data-driven insights, and advanced automation. Together, we’re building the foundation for the world’s next generation of clean energy infrastructure.

Nextpower is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

We are Nextpower

Top Skills

Azure
Databricks
Delta Lake
Kafka
Python
Spark
SQL
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The Company
Fremont, CA
1,107 Employees

What We Do

Since day one, Nextracker’s mission has been to transition the world to affordable, renewable power, by developing the highest-performing and resilient solar tracking technologies and software in the market for our customers.
From sustainable tracker solutions that conform to uneven terrain and withstand extreme weather, Nextracker systems have resilience built in. Nextracker leads the solar industry with solar tracker technologies that optimize and increase energy production while reducing costs for significant plant ROI

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