Senior Data Engineer

Title: Senior Data Engineer

Location: Orlando, FL 

Duration: 24 Months Contract w2

Role Summary:

• The Senior Data Engineer – B2B AI & Data Products will lead the design, development, and implementation of B2B integrated data solutions that power analytics, reporting, and AI-driven experiences. This role will be responsible for creating trusted, scalable data foundations while enabling next-generation self-service capabilities through AI-powered applications, conversational agents, semantic search, and intelligent data products.
• Working across business, product, analytics, and technology teams, this role will architect and engineer a modern integrated data ecosystem that makes information more accessible, discoverable, and actionable. The ideal candidate combines deep data engineering expertise with hands-on experience enabling AI and generative AI solutions within data ecosystem

• Minimum Qualifications:

  • 7+ years of experience in data engineering, data architecture, or enterprise data platform development.
  • Proven experience designing and supporting enterprise data pipelines and data warehouse / Lakehouse solutions.
  • Strong expertise in SQL and Python.
  • Experience with cloud data platforms (e.g., Snowflake, AWS, Azure) and hybrid data integration patterns.
  • Hands-on experience with ETL / ELT orchestration tools and data pipeline automation.
  • Strong understanding of data modeling, semantic layer design, and performance optimization techniques.
  • Experience developing solutions that support Generative AI, LLMs, AI Assistants, Copilots, or Conversational AI applications.
  • Experience designing data architectures for Retrieval-Augmented Generation (RAG) or semantic search solutions.
  • Familiarity with vector databases, embeddings, semantic indexing, and knowledge retrieval architectures.
  • Experience integrating structured and unstructured enterprise data sources to support AI-driven applications.
  • Strong understanding of AI governance, prompt engineering concepts, model evaluation, and responsible AI practices.
  • Experience with modern AI frameworks and services such as Claude, Cursor, Snowflake Cortex AI, Databricks Mosaic AI, Amazon Bedrock, or equivalent technologies.
  • Experience implementing metadata-driven architectures that improve data discoverability and AI consumption.
  • Experience supporting BI and analytics platforms such as Power BI, Tableau, or similar tools.
  • Familiarity with data governance, metadata management, and data quality frameworks.
  • Ability to collaborate effectively across product teams, engineering disciplines, and business stakeholders.
  • Strong analytical thinking, problem-solving capability, and communication skills.

   

  Preferred Qualifications:

  • Experience supporting enterprise data product models or platform-based operating structures.
  • Hands-on experience enabling AI or machine learning workflows within enterprise data environments, including support for model data pipelines, intelligent data products, or automated insight generation.
  • Experience supporting AI product development from concept through production deployment.
  • Experience building enterprise conversational agents, AI assistants, or knowledge retrieval platforms.
  • Hands-on experience implementing RAG architectures and vector search platforms.
  • Experience with GraphRAG, knowledge graphs, semantic modeling, or enterprise ontologies.
  • Experience enabling natural language interaction with business datasets and analytics platforms.
  • Experience using agents and orchestration frameworks such as LangGraph, Semantic Kernel, CrewAI, AutoGen, or similar technologies.
  • Experience partnering with Product Managers to deliver AI-driven self-service capabilities.
  • Exposure to machine learning data preparation, AI data pipelines, or advanced analytics environments.
  • Experience implementing data observability or data reliability engineering practices.
  • Background working in Agile delivery models with cross-functional product teams.