Senior Data Engineer - AI Data Products & Enablement

Creative Solutions Services, LLC

Orlando (FL)

On-site

USD 120,000 - 160,000

Full time

6 days ago

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Job summary

Software Resources in Orlando is seeking a Senior Data Engineer (B2B AI & Data Products Enablement) to lead the design, development, and implementation of integrated data solutions powering analytics, reporting, and AI-driven experiences.

The role emphasizes scalable data foundations, self-service AI, semantic search, and governance, partnering with business, product, analytics, and technology teams to deliver trusted data assets for AI-enabled solutions.

Qualifications

7+ years in data engineering or enterprise data platform development.
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.

Responsibilities

Design and optimize scalable data pipelines in the DXT ecosystem.
Architect data ingestion, transformation, and storage across cloud and hybrid environments.
Establish reusable data engineering standards and best practices for consistency and scalability.
Develop curated enterprise datasets for dashboards, analytics, and AI initiatives.
Design data architectures to support enterprise AI applications and semantic search.
Build and maintain Retrieval-Augmented Generation (RAG) frameworks and semantic search capabilities.
Engineer scalable solutions that unify structured and unstructured data for AI-ready environments.
Collaborate with business stakeholders to translate data needs into AI-enabled solutions.
Enable enterprise users to access, understand, and trust data via conversational and self-service interfaces.
Design vectorized data architectures and embeddings for LLM-based applications.
Work with AI and analytics teams to operationalize AI-driven use cases with governance and security.