Job Description
Passionate team members, challenging projects and a great place to work! This is what you can expect if you join the Quisitive team. Founded in 2016, Quisitive is a global Microsoft services and solutions partner. We are a team of professionals with a strong reputation for successfully delivering award-winning Microsoft solutions, including being named Microsoft’s 2024 Analytics Partner of the Year. Our culture of continual learning and innovation ensures that we remain committed to Microsoft’s long-term strategy.
What do we attribute our award-winning success to? The people we hire, of course! Our team members join Quisitive for more than just a job. They come to Quisitive to contribute to something bigger than themselves – to be part of a high-performing culture, continue their infinite quest to learn, and deliver innovative and exciting solutions that impact both Quisitive’s and our customers’ future success. Our leaders continuously strive to provide the tools and resources that you need to do what you do best each and every day!
We are currently hiring a Sr. Data Engineer with strong AI experience to join our team and help build the backbone of our data-driven solutions. This role is perfect for someone who loves working with large-scale data, optimizing pipelines, and exploring cutting-edge AI technologies. You’ll play a key role in designing and maintaining systems that power intelligent applications and knowledge management platforms.
This role can be located anywhere in the United States.
What will this role entail?
- 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
What’s required to be successful in this role?
- 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
We are looking for curious initiative takers to join our team, so if you are passionate about working with smart people that are committed to accomplishing great things, then apply today!
Please, no third-party agency inquiries, and we are unable to offer visa sponsorships at this time.
About Quisitive
With significant growth since 2016, Quisitive is rapidly achieving our vision of becoming the leading global Microsoft partner as we continue to expand across the United States, Canada and India. With a diversified delivery model that includes both nearshore and offshore capabilities, our team of Microsoft experts delivers cloud and artificial intelligence business solutions and services that ensure our customers achieve their digital transformation goals. In addition, Quisitive offers a portfolio of industry-focused solutions that address customer challenges in healthcare, manufacturing, state & local government and performance management.
