Senior Data & AI Engineer — Build Data Pipelines

Intapp; Charlotte (NC); Híbrido; USD 120.000 - 180.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work (Partial remote)

Free lunches and kitchens

Wellness programs

Volunteer time off

Donation matching

Descripción de la vacante

Intapp is seeking a Senior Data and AI Engineer to own data pipelines from source to model, using Python and dbt, and to deploy on Docker and Kubernetes in AWS. You will build MCP servers to provide governed access to enterprise data and tools, and run agentic AI workflows in production with strong emphasis on security and observability.

You will collaborate with business teams to deliver reliable, scalable data/AI solutions, review code, and raise engineering standards while mentoring peers.

Formación

• 8+ years of professional data engineering experience.
• Strong Python for data processing and services, plus dbt experience.
• Hands-on Docker and Kubernetes for deployment and scaling.
• Solid AWS experience across core services.
• Advanced SQL and data modeling skills.
• Experience with Model Context Protocol (MCP) or similar LLM interfaces.
• Nice to have: Airflow orchestration, Redshift/Snowflake/BigQuery, CRM/ERP data sources.

Responsabilidades

• Design, build, and operate data pipelines from source to model using Python and dbt.
• Containerize workloads with Docker and deploy on Kubernetes with CI/CD.
• Develop MCP servers/connectors for governed access to data and tools.
• Deploy and monitor agentic workflows, including tool calls and evaluation.
• Collaborate with business teams to translate requests into scalable data/AI solutions.
• Mentor engineers and improve design, testing, and documentation standards.

Conocimientos

Python

dbt

Docker

Kubernetes

AWS

SQL

Model Context Protocol

LLM tooling

Educación

Bachelor's degree in CS/Engineering

Herramientas

Docker

Kubernetes

Descripción del empleo

Intapp is seeking a Senior Data and AI Engineer to own data pipelines from source to model, using Python and dbt, and to deploy on Docker and Kubernetes in AWS. You will build MCP servers to provide governed access to enterprise data and tools, and run agentic AI workflows in production with strong emphasis on security and observability.

You will collaborate with business teams to deliver reliable, scalable data/AI solutions, review code, and raise engineering standards while mentoring peers.