Automation Developer II
About the position This position is hybrid in Cincinnati, Ohio and sits within our Content division which identifies and publishes accurate and relevant project data for our software solutions. The Opportunity We are seeking an experienced Automation Developer II to design, build, and scale backend and serverless solutions that drive efficiency, data quality, and system interoperability across the organization. This role is ideal for a developer who has mastered foundational backend skills and is ready to lead mid-sized projects, mentor peers, and contribute to architecture and best practices. The ideal candidate combines strong technical proficiency in Python or another general-purpose language with the ability to translate business needs into scalable, reliable cloud solutions.
Responsibilities
- Design and implement backend and serverless services—primarily on Google Cloud Platform (GCP)—to improve operational efficiency and data accuracy. Typical components include Cloud Run/Cloud Functions, Pub/Sub, Cloud Scheduler, Cloud Storage, Firestore/Datastore, and BigQuery.
- Build and integrate APIs and microservices that enable seamless data exchange across ConstructConnect’s platforms (REST; authentication, rate limiting, pagination, and versioning).
- Develop event-driven and batch workflows (Pub/Sub, Cloud Tasks, Cloud Workflows), plus ad-hoc scripting for data processing, migrations, and operational tooling.
- Leverage AI/ML where appropriate (e.g., LLM-enabled services, lightweight NLP pipelines) to enhance decision-making and process intelligence.
- Own the full delivery lifecycle: requirements, solution design, development, testing, deployment, observability, and iterative optimization.
- Instrument, monitor, and troubleshoot services using Cloud Logging, Cloud Monitoring, Error Reporting, and tracing to ensure reliability and performance.
- Champion security and governance (IAM, Secret Manager, VPC/SVPC, least-privilege patterns, data retention).
- Mentor Level I developers via code reviews, pairing, and reusable patterns; contribute to internal guides and templates.
- Partner with stakeholders to identify high-impact opportunities, define ROI, and prioritize work that delivers measurable results.
- Document code, architectures, runbooks, and reusable components in our internal knowledge base.
- This job description in no way implies that the duties listed here are the only ones that team members can be required to perform.
Requirements
- Bachelor’s degree in computer science, Engineering, or related field OR 3–5 years of professional experience delivering backend/serverless solutions.
- Proficiency in Python or another general-purpose language (e.g., Java or Node.js) with a strong understanding of data structures, modular design, testing, and package management.
- Experience designing and integrating RESTful APIs for system interoperability.
- Hands-on experience with GCP serverless services (Cloud Run or Cloud Functions) and eventing (Pub/Sub, Cloud Scheduler, Cloud Tasks).
- Familiarity with deploying AI/ML integrations (LLMs, basic NLP, or model inference endpoints) within backend workflows.
- Experience with ETL/data pipelines (BigQuery, Dataflow/Beam or equivalent), workflow orchestration, and performance optimization.
- Strong analytical and problem-solving skills with a focus on scalability, reliability, and maintainability.
- Excellent communication and collaboration skills with cross-functional teams.
- Ability to lead smaller projects or own technical workstreams within larger initiatives.
Nice-to-haves
- Depth with GCP (IAM, VPC, Secret Manager, Cloud Build, Artifact Registry) and cloud-native design patterns.
- Infrastructure as Code (Terraform) and CI/CD workflows (Cloud Build, GitLab CI).
- Proficiency with SQL and data modeling; experience with BigQuery performance tuning.
- Experience building modular, reusable components/libraries and adopting clean architecture.
- Knowledge of security and compliance best practices for APIs, data, and access management.
- Observability experience (structured logging, metrics, traces, SLOs/error budgets).
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