Job Title: Databricks Full Stack Engineer
Location: Remote
Contract: 12 Months – Possible for extension
Job Overview
The Full Stack Engineer is expected to design and build end-to-end data and AI applications using Databricks-native functionality. After understanding the business context, you will deliver production-grade solutions that span the data layer, the application layer, and the user experience, using Databricks Apps, Genie, the Lakehouse, and Lakebase as core building blocks.
This role is for individuals passionate about turning data into usable products. You will work directly with clients and with the team’s product managers, data engineers, and AI/ML engineers to translate business needs and feature requirements into well-architected, secure, and scalable applications. You will be responsible for the execution of our established delivery methodology, and you will help clients understand what is possible on the Databricks platform as they shape their future roadmap.
It is a key part of the role to explain technical designs and trade-offs in non-technical terms. The Full Stack Engineer will interface with Perficient technical and business delivery personnel, as well as vendors and customers on a regular basis.
Qualifications:
- Minimum 5 years of working experience as a full stack, data, or software engineer, with strong proficiency in Python and SQL.
- Minimum 2 years of hands-on Databricks experience, including Delta Lake, Unity Catalog, Databricks SQL, and Apache Spark.
- Hands-on experience building and deploying applications on Databricks Apps and working knowledge of Genie and Lakebase (or PostgreSQL with strong ability to ramp up on Lakebase).
- Proficiency in front-end development (JavaScript/TypeScript, React or similar) and back-end/API development (FastAPI, Flask, or similar).
- Minimum 2 years of cloud platforms experience deploying data and application workloads on AWS, Azure, or Google Cloud Platform.
- Hands-on experience with at least one LLM and an orchestration library, i.e., LangChain, LangGraph, LlamaIndex, or HuggingFace.
- Strong understanding of data modeling, relational and Lakehouse design, and ETL/ELT pipeline development.
- Experience with CI/CD, Git-based workflows, infrastructure-as-code, and Databricks Asset Bundles.
- Understanding of application security, identity and access management, and data governance best practices.
- Experience in complete project life cycle activities on development and maintenance projects.
- Knowledge and experience in developing software using agile methodologies.
- Proven track record of technical roles delivering solutions within defined timeframes.
- Excellent written and oral communication skills; ability to communicate effectively with technical and non-technical staff.
- Experience with authoring, editing, and presenting technical documents.
- Bachelor’s degree in computer science, Engineering, Information Systems, or a related field.
- Must be open to travel and work at client site when required.
