Intapp

Senior AI & Data Engineer

Intapp

full-time

Posted on:

Location Type: Hybrid

Location: Palo Alto • California • North Carolina • United States

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Job Level

Senior

Tech Stack

AirflowAmazon RedshiftAWSCloudDockerEC2ETLKubernetesPandasPySparkPythonSQLTerraform

About the role

  • Design and implement robust, scalable ETL/ELT pipelines to ingest, transform, and deliver data across the organization
  • Build and maintain data models optimized for analytical workloads and downstream consumption
  • Develop reusable frameworks and libraries to accelerate data engineering workflows
  • Architect and manage cloud-native data solutions on AWS, leveraging services such as S3, EC2, ECS, ECR and EventBridge
  • Deploy and orchestrate containerized workloads using Docker and Kubernetes in production environments
  • Implement infrastructure-as-code practices using Terraform, CloudFormation, or similar tools
  • Design and optimize data warehouse architectures using Redshift or Snowflake
  • Manage data lifecycle, governance, and cost optimization within warehouse environments
  • Explore and integrate AI agents and Model Context Protocol (MCP) patterns into data workflows where applicable
  • Collaborate with AI/ML teams to ensure data infrastructure supports model training, inference, and feature engineering needs
  • Participate in architectural decisions and contribute to the data platform roadmap

Requirements

  • 7+ years of professional experience in data engineering or related roles
  • Advanced proficiency in Python including data libraries (pandas, PySpark, SQLAlchemy), testing frameworks, and packaging
  • Strong hands-on experience with Docker and Kubernetes (EKS, GKE, or self-managed clusters)
  • Deep expertise with Redshift or Snowflake, including performance tuning, data modeling, and administration including DBT
  • Extensive experience across the AWS ecosystem, particularly data-related services (S3, Glue, Lambda, IAM, VPC, CloudWatch)
  • Expert-level SQL skills for complex analytical queries and data transformations
  • Experience with workflow orchestration tools (Airflow, Dagster, etc.)
  • Familiarity with version control (Git), CI/CD pipelines, and agile development practices
  • Strong understanding of data governance, security, and compliance principles
Benefits
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Applicant Tracking System Keywords

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Hard Skills & Tools
ETLELTdata modelingPythonSQLDockerKubernetesRedshiftSnowflakeSQLAlchemy
Soft Skills
collaborationarchitectural decision-makingproblem-solvingcommunicationdata governancecost optimizationagile development