Senior Data Engineer – AI Solutions

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November 24

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Quisitive

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SaaS • Consulting • Enterprise

Quisitive is a leading Microsoft Cloud Partner that focuses on providing integration and consulting services to help businesses innovate and thrive using Microsoft cloud technologies. The company specializes in application development, data and analytics, artificial intelligence, business applications, security, digital workplace solutions, and infrastructure management. Quisitive assists organizations in various sectors, including manufacturing, healthcare, education, energy, and public sector, helping them efficiently navigate and implement cloud-based solutions. With tailored products like MazikCare for healthcare and ShopFloor for manufacturing, Quisitive enhances operational efficiency and drives digital transformation across its clients’ businesses.

501 - 1000 employees

☁️ SaaS

🏢 Enterprise

📋 Description

• Building and maintaining backend data ingestion and embedding pipelines • Setting up environments, clone repositories, and running pipelines in JupyterHub • Working on large-scale ETL processes, including converting Iceberg tables to Parquet and exporting data to S3 buckets • Designing and optimizing schemas for Neo4j-based graph solutions • Integrating knowledge workflows and KB articles into graph structures for advanced retrieval • Troubleshooting data quality issues and optimizing Spark jobs for efficiency • Implementing retry mechanisms and debugging full-stack issues related to large file operations • Managing secure access using JWT and Kerberos authentication • Handling credentials for Oracle DB and API clients via HashiCorp Vault • Working with GitLab for source control and Jira for project tracking • Supporting migration efforts from Azure DevOps to GitLab/Jira environments

🎯 Requirements

• Strong proficiency in Python for data processing and pipeline development • Hands-on experience with Spark, Iceberg, and large-scale data frameworks • Familiarity with Neo4j, LangChain, and LLM integration for AI-driven solutions • Experience with Oracle DB, PostgreSQL, and PGVector for embedding strategies • Comfortable working with S3 buckets, Parquet, and CSV formats • Exposure to embedding models like BGEM 3 and Nomic • Understanding of AI-powered retrieval and recommendation systems • JupyterHub for testing/debugging • Power BI for dashboard development and reporting • Knowledge of Kerberos authentication and secrets management with HashiCorp Vault

🏖️ Benefits

• Passionate team members • Challenging projects • A great place to work