
Forward Deployed Engineer with Databricks & Cursor
About the Role
We are looking for a Forward Deployed Engineer with strong hands-on experience in Databricks and AI-assisted software development using Cursor. The role is suited for an engineer who can work directly with clients and internal teams to understand business problems, rapidly build solutions, and take them from prototype to production.
The ideal candidate should have strong expertise in Python, SQL, Databricks, PySpark, data engineering, APIs, and modern AI-assisted development workflows, along with excellent problem-solving and client-facing skills.
Key Responsibilities
Forward Deployed Engineering
- Work directly with clients and stakeholders to understand business and technical requirements.
- Translate business problems into scalable technical and data solutions.
- Rapidly prototype, test, iterate, and productionize solutions.
- Collaborate with engineering, data, AI, and delivery teams to implement customer solutions.
- Troubleshoot production issues and continuously improve deployed solutions.
- Act as a technical bridge between clients and internal engineering teams.
Databricks & Data Engineering
- Design and develop scalable data solutions using Databricks, PySpark, Python, and SQL.
- Build and optimize ETL/ELT and data processing pipelines.
- Work with Databricks Lakehouse, Delta Lake, Unity Catalog, and Databricks Workflows.
- Develop data ingestion and transformation pipelines for structured and semi-structured data.
- Optimize Databricks workloads for performance, scalability, reliability, and cost.
- Integrate Databricks with databases, APIs, cloud platforms, and enterprise applications.
Cursor & AI-Assisted Development
- Use Cursor and AI-assisted development workflows to accelerate software development, debugging, refactoring, and documentation.
- Effectively use AI coding assistants to understand existing codebases and develop new features.
- Apply appropriate engineering judgment to review, validate, test, and secure AI-generated code.
- Use AI-assisted development for rapid prototyping and proof-of-concept development.
- Work with modern AI/LLM APIs and tools where required for customer solutions.
- Stay current with emerging AI-assisted software engineering practices.
Production & Deployment
- Develop production-ready applications, APIs, and data pipelines.
- Work with Git, CI/CD, APIs, containers, and cloud environments.
- Monitor application and pipeline performance and resolve production issues.
- Ensure solutions meet requirements for scalability, security, reliability, and maintainability.
- Collaborate with Data Scientists and ML Engineers to integrate AI/ML capabilities into production systems.
Required Skills & Experience
- 4+ years of experience in Software Engineering, Data Engineering, AI Engineering, or a related field.
- Strong hands-on experience with Databricks.
- Strong proficiency in Python, PySpark, and SQL.
- Experience with Delta Lake and Lakehouse architecture.
- Experience building production-grade data pipelines.
- Hands-on experience with Cursor or similar AI-powered coding assistants.
- Strong understanding of REST APIs and system integrations.
- Experience working with cloud platforms such as AWS, Azure, or GCP.
- Strong debugging, problem-solving, and analytical skills.
- Excellent communication and client-facing abilities.
Preferred Skills
- Experience with Databricks Unity Catalog, Workflows, and MLflow.
- Experience with Generative AI / LLM applications.
- Knowledge of Claude, OpenAI, Azure OpenAI, or other LLM platforms.
- Experience with RAG, vector databases, embeddings, or AI agents.
- Experience with Docker, Kubernetes, and CI/CD.
- Experience in a consulting, customer-facing engineering, or professional services environment.
- Exposure to Agile/Scrum methodologies.
Key Competencies
- Strong problem-solving and ownership mindset
- Ability to work in ambiguous and fast-paced environments.
- Strong client/stakeholder management skills.
- Ability to understand business requirements and convert them into technical solutions.
- Strong communication and presentation skills.
- Ability to rapidly learn new technologies and tools.
- Comfortable working with AI-assisted development while maintaining high engineering standards.
Education
- Bachelor's or master’s degree in computer science, Information Technology, Engineering, Data Science, or a related discipline.

About Ampera Technologies
About
At Ampera Technologies, we empower businesses with cutting-edge data analytics, quality assurance, and data engineering solutions
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