Data Engineer (STRICTLY OUR W2 -- Do NOT respond if you're looking for C2C)

InfoWeb Systems Inc. has the following requirement with our direct client, John Deere. If you feel that you’re a good fit and interested in this position please respond with your WORD formatted resume or give me a call. If you were offered this position you would be required to become an InfoWeb W2 employee… NO Corp to Corp.

Location:             REMOTE

Duration:             1+ years to LONG term

Rate:                     DOE/hr on OUR W2

**Online Glider assessment will be as part of the submittal process!

Senior Software Engineer – Data Products & Cloud Solutions
Remote / Onsite They would like someone who is able to come onsite if needed.

Description
We are looking for a highly technical Senior Software Engineer to join the Compass team and help design, build, deploy, and support production data products and services for precision agriculture.
The Compass team develops software and infrastructure that turns machine, agronomic, geospatial, logistics, and other data into production capabilities. Our work spans backend APIs, event-driven data pipelines, cloud infrastructure, databases, Databricks integrations, monitoring, and operational tooling.

We are looking for someone who is comfortable working across technologies, can independently solve ambiguous technical problems, and can take a capability from initial design through production deployment and support. This role will work closely with software engineers, data scientists, product teams, and partner engineering teams.

Essential Attributes / Experience
• Excellent Python development skills with production software deployment experience
• Strong experience designing and developing REST APIs, backend services, and data-processing applications
• Strong understanding of AWS, including services such as Lambda, API Gateway, IAM, S3, SQS, EventBridge, and RDS/Aurora
• Experience with relational databases, particularly PostgreSQL
• Experience building and maintaining Infrastructure as Code, preferably Terraform
• Experience with CI/CD, automated testing, and Git/GitHub development practices
• Strong troubleshooting skills across application, data, infrastructure, and integration layers
• Ability to independently investigate complex problems, propose solutions, and deliver production-quality implementations
• Strong communication skills and ability to work across engineering, data science, product, and business teams
• Experience improving systems for scalability, reliability, security, performance, and cloud cost efficiency
Preferred Attributes
• Experience with Databricks, Spark, PySpark, SQL, Delta Lake, or similar data platforms
• Experience with event-driven and serverless architectures
• Experience with Docker and containerized applications
• Experience with DBMate, Pydantic, AWS Lambda Powertools, or similar Python frameworks
• Experience with authentication and authorization patterns such as AWS IAM and OAuth/OIDC
• Experience with observability platforms such as Datadog
• Experience processing machine, agricultural, logistics, or other high-volume data
• Experience with GitHub Actions and automated cloud deployments
Example Responsibilities (Including but not limited to):
• Architect and implement new AWS and Databricks-based solutions while improving existing Compass services for scalability, reliability, and maintainability
• Design, build, and maintain Python REST APIs, Lambda functions, backend processes, and event-driven services
• Build pipelines that ingest, transform, process, and persist machine, agronomic, geospatial, logistics, and other data
• Build and maintain AWS infrastructure using Terraform
• Design and support PostgreSQL/Aurora databases, including schemas, migrations, application connectivity, and performance
• Build solutions supporting both real-time/event-driven workloads and scheduled batch processing
• Develop and support Databricks integrations and data-processing workflows as needed by Compass products
• Create and maintain CI/CD pipelines using GitHub Actions, including automated testing and application/infrastructure deployment
• Implement and improve logging, metrics, dashboards, monitoring, and alerts using Datadog
• Troubleshoot production issues across APIs, databases, queues, cloud infrastructure, data-processing jobs, and external integrations
• Identify opportunities to improve system performance, scalability, reliability, and cloud cost

Thanks!

Mary

Mary Loney Bichell

InfoWeb Systems, Inc.