Data Software Engineer

Job Description

We’re hiring for a Data Software Engineer to support the development of robust, scalable applications and data pipelines that power AI/ML initiatives. This is a hands-on role combining software engineering, data infrastructure, and ML workflow enablement in a modern cloud-native environment. The ideal candidate has strong backend development experience (Python, GCP) and is confident navigating complex systems across dev and prod environments.Responsibilities:Software Engineering & Backend Development

• Design and deploy scalable Python applications using GCP services like Cloud Run, Kubernetes, and Compute Engine.

• Develop APIs, microservices, and core backend systems to support application and AI/ML use cases.

• Debug and resolve production issues across distributed systems, data pipelines, and orchestration layers.

• Build and maintain robust data transformation logic using DBT.

• Develop and orchestrate CDC data ingestion pipelines using Debezium and Airflow.

Infrastructure & Platform Support

• Monitor production environments and contribute to platform reliability and scalability.

• Implement improvements based on technical backlog priorities.

• Support both analytics and ML infrastructure through architectural contributions and automation.

AI/ML Workflow Enablement

• Build and support pipelines for model training, batch inference, feature generation, and performance monitoring.

• Coordinate automated model refresh cycles and scoring jobs using Airflow or custom orchestration.

• Ensure ML pipelines produce structured and reusable features for analytics and conversational AI agents.

Cross-Functional Collaboration

• Partner with functional consultants, analysts, and AI/ML engineers to define and deliver technical solutions.

• Participate in discovery and planning sessions to align technical architecture with business needs.

• Contribute to solutioning sessions and client-facing discussions with clear and structured technical input.

Qualifications:

• 3–6 years of experience in software development or data engineering roles.

• Strong proficiency in Python for backend and data application development.

• Hands-on experience with Google Cloud Platform (e.g., Cloud Run, Kubernetes, Compute Engine, BigQuery, Cloud SQL, Composer).

• Experience with DBT, Airflow, and Debezium (CDC).

• Proven ability to troubleshoot complex systems, optimize DAG performance, and manage orchestration dependencies.

• Familiarity with Git-based workflows, CI/CD, and DevOps best practices.

• Exposure to enabling ML workflows (e.g., model scoring, data prep, feature pipelines).

• Comfort working in fast-paced, ambiguous environments with shifting technical requirements.

• Basic front-end development skills (e.g., React, Angular, or plain HTML/CSS/JS) to support lightweight UIs.

Preferred Qualifications:

• Java experience for enterprise integration or backend system development.

• Familiarity with ML orchestration frameworks such as Vertex AI Pipelines, Kubeflow, or MLflow.

• Experience supporting LLM systems or agent frameworks (e.g., LangChain, CrewAI, LlamaIndex).

• Experience with infrastructure-as-code tools (e.g., Terraform or Pulumi).

• Prior consulting or client-facing delivery experience.

• Familiarity with translating functional requirements into technical infrastructure for analytics and AI use cases.