NAVA Software solutions is looking for a Databricks Developer.
Details:
Application Developer Databricks Apps
Location: Spring, TX (Hybrid)
Duration: 6-12 months
Position Summary
We are seeking an Application Developer to design, build, and deploy interactive data and AI applications on the Databricks platform using Databricks Apps. This role sits at the intersection of application engineering and the Lakehouse - building user-facing tools that put governed data, ML models, and GenAI capabilities directly into the hands of business users.
We are looking for a modern, AI-native developer: someone with strong full-stack fundamentals (Python backend focus) who leverages AI coding assistants such as Claude, GitHub Copilot, and Databricks Assistant to accelerate delivery - and who has the engineering judgment to critically review, test, and secure AI-generated code. Framework-specific experience matters less than fundamentals; a strong engineer with sound API, authentication, and data-access instincts can ramp quickly on any supported framework.
Key Responsibilities
Application Development
Design and develop production-grade applications on Databricks Apps using Python frameworks such as Streamlit, Dash, Gradio, Flask, or FastAPI (or React/Node.js where appropriate)
Build intuitive, responsive UIs for data exploration, ML model interaction, GenAI/agentic workflows, and operational dashboards
Integrate applications with lakehouse assets - Delta tables, Unity Catalog-governed data, SQL Warehouses, Model Serving endpoints, and Vector Search indexes
Implement app-level state management, caching, and performance optimization for concurrent multi-user workloads
Platform Integration & Data Access
Develop against Databricks REST APIs and SDKs (Python SDK, Databricks Connect) for jobs, serving endpoints, and workspace resources
Build secure data access patterns using service principals, on-behalf-of-user authorization, and Unity Catalog permissions
Connect applications to backend services including Lakebase (Postgres), SQL Warehouses, and external APIs where required
Security, Governance & Deployment
Apply enterprise security standards: OAuth/SSO integration, secret management via Azure Key Vault-backed secret scopes, and least-privilege access design
Manage application lifecycle across development, staging, and production environments using CI/CD (Databricks Asset Bundles, Azure DevOps, or GitHub Actions)
Ensure applications comply with data governance, audit, and access-control policies defined in Unity Catalog
AI-Accelerated Engineering
Use AI coding assistants (Claude, GitHub Copilot, Databricks Assistant) as a core part of the development workflow to accelerate design, implementation, testing, and documentation
Apply rigorous review to AI-generated code: validate security posture, data-access boundaries, error handling, and performance before promotion
Develop precise, well-structured specifications and prompts that translate business requirements into working application components
Champion responsible AI-assisted development practices across the team, including standards for testing and validating generated code
Collaboration & Support
Partner with Data Engineering, Data Science, and BI teams to expose pipelines, models, and analytics through application interfaces
Gather requirements from business stakeholders and translate them into functional application designs
Provide production support, monitoring, and iterative enhancement of deployed applications
Required Qualifications
Bachelor's degree in Computer Science, Engineering, or a related field
4+ years of software/application development experience, including full-stack development with a Python backend focus (APIs, authentication, databases, web application fundamentals)
Demonstrated experience using AI coding assistants (Claude, GitHub Copilot, Databricks Assistant, or similar) in a professional development workflow, with the judgment to critically review, test, and secure AI-generated code
Strong grasp of REST API design, request/response lifecycles, and authentication/authorization patterns (OAuth 2.0, service principals, RBAC)
Strong SQL skills and experience working with relational databases and/or Delta Lake / lakehouse architectures
Working experience with Databricks (Azure Databricks preferred): notebooks, SQL Warehouses, Unity Catalog, Model Serving
Experience with Git-based workflows and CI/CD pipelines
Preferred Qualifications
Direct experience building and deploying Databricks Apps in production
Hands-on experience with one or more supported frameworks: Streamlit, Dash, Gradio, Flask, FastAPI, or React/Node.js (specific frameworks are learnable; fundamentals are required)
Experience integrating GenAI capabilities - LLM endpoints, RAG patterns, Vector Search, or agent frameworks (LangGraph, LangChain)
Familiarity with Lakebase or Postgres-backed application state
Experience with Azure services: Key Vault, Entra ID, Azure Data Factory, Azure DevOps
Databricks certification (Data Engineer Associate, Generative AI Engineer Associate, or similar)
Experience in regulated or engineering-driven industries (maritime, energy, manufacturing)
What Success Looks Like in the First Year
Delivers 2 3 production Databricks Apps serving internal business users with governed data access
Establishes reusable application templates, deployment patterns, and CI/CD standards for the team - including practices for AI-assisted development
Becomes the go-to resource for app-layer integration with the lakehouse and model serving infrastructure
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