Software Engineer

Sunrise Systems; Edison (CA); On-site; USD 140,000 - 180,000; Full time

Job summary

Sunrise Systems is seeking a Senior Software Engineer to contribute to data processing pipelines for an AI-enabled analytics product targeting Large AG customers. The role is onsite in the San Francisco Bay Area or Des Moines Metro Area and spans a 6-month engagement.

You will design AWS/Databricks solutions to process geospatial data, develop REST APIs with Lambda, and manage Terraform-based infrastructure. Collaboration with product managers, data scientists, and field teams is essential.

Qualifications

• 5+ years of professional software development with Python.
• Hands-on AWS and Databricks in production environments.
• Experience deploying cloud-native solutions in fast-paced teams.
• Strong communication and stakeholder management.

Responsibilities

• Design and implement AWS/Databricks solutions to process large geospatial datasets for real-time API services.
• Develop and maintain REST APIs and backend processes using AWS Lambda.
• Build infrastructure as code using Terraform.
• Set up and maintain CI/CD pipelines using GitHub Actions.
• Optimize system performance and workflows to improve scalability and reduce cloud costs.
• Enhance monitoring and alerting across systems using Datadog.
• Support field testing and customer operations by debugging and resolving data issues.
• Collaborate with product managers and end users to understand requirements, build backlog, and prioritize work.
• Work closely with data scientists to productionize prototypes and proof-of-concept models.

Skills

Python

Test-driven development

Communication

Cloud computing

REST APIs

Tools

AWS

Databricks

Terraform

GitHub Actions

Datadog

PySpark

Job description

Software Engineer

Location: Onsite Candidates may be based in either the San Francisco Bay Area or the Des Moines Metro Area,

6 Months

Description:

We are seeking a highly technical and self-directed Senior Software Engineer to contribute to the development of data processing pipelines for a new AI-enabled data analytics product targeted at Large Ag customers.

Ideal candidates will have:

• 5+ years of professional software development experience using Python


• 2+ years of hands-on experience with AWS and Databricks in production environments

We are looking for mid-career professionals with a proven track record of deploying cloud-native solutions in fast-paced software delivery environments.

In addition to technical expertise, successful candidates will demonstrate:

• Strong communication skills, with the ability to clearly articulate technical concepts to both technical and non-technical stakeholders (this is extremely important - please vet out accorrdingly)


• The ability to work effectively with limited supervision in a distributed team environment


• A proactive mindset, adaptability, and a commitment to team success

Key Responsibilities:

• Design and implement AWS/Databricks solutions to process large geospatial datasets for real-time API services


• Develop and maintain REST APIs and backend processes using AWS Lambda


• Build infrastructure as code using Terraform


• Set up and maintain CI/CD pipelines using GitHub Actions


• Optimize system performance and workflows to improve scalability and reduce cloud costs


• Enhance monitoring and alerting across systems using Datadog


• Support field testing and customer operations by debugging and resolving data issues


• Collaborate with product managers and end users to understand requirements, build backlog, and prioritize work


• Work closely with data scientists to productionize prototypes and proof-of-concept models

Required Skills & Experience:

• Excellent coding skills in Python with experience deploying production-grade software


• Strong foundation in test-driven development


• Solid understanding of cloud computing, especially AWS services such as IAM, Lambda, S3, RDS


• Professional experience building Databricks workflows and optimizing PySpark queries

Preferred Experience:

• Experience working with geospatial data and related libraries/tools


• Experience building and operating API using AWS lambda


• Familiarity with data lake architectures and Delta Lake


• Experience with event-driven architectures and streaming data pipelines (e.g., Kafka, Kinesis)


• Exposure to ML Ops or deploying machine learning models in production


• Prior experience in cross-functional teams involving product, data science, and backend engineering teams