AI Data Engineer

Overview

On Site
Depends on Experience
Contract - Independent
Contract - W2

Skills

ADF
Analytics
Artificial Intelligence
Attention To Detail
Business Intelligence
Cloud Computing
Clustering
Collaboration
Conflict Resolution
DAX
English
Machine Learning (ML)
Data Modeling
Data Quality
Data Storage
Data Structure
Data Warehouse
Microsoft Azure
Microsoft Power BI
Normalization
Optimization
Problem Solving
Programming Languages
Python
Query Optimization
SQL
Semantics
Snow Flake Schema
Spring Framework
Star Schema
Training
R
Training And Development
Visualization
Workflow

Job Details

Job Title:- AI Data Engineer Location:- Spring Texas (On-Site) Job Type:- Long Term Contract
Need Only Local
 Primary skill set (mandatory technical skill sets) :
The ideal candidate will have experience working with medium to complex data structures in a corporate environment. They should be proficient in working hands-on with data in Snowflake, transforming data with DBT, and visualizing it efficiently in Power BI, including implementing logic in DAX. Additionally, the candidate should possess strong problem-solving skills, attention to detail, and the ability to communicate complex technical concepts to both technical and non-technical stakeholders in English.
AI Engineering Responsibilities:

  • Collaborate with data modelers to prepare and optimize datasets for AI model training and inference.
  • Design and implement data pipelines that support AI/ML workflows, including feature engineering and model monitoring.
  • Integrate AI-powered analytics and predictive models into business intelligence tools like Power BI.
  • Evaluate and implement AI services (e.g., Azure Cognitive Services, OpenAI, or custom ML models) to enhance data products and user experiences.

Required Skills and Experience

  • SQL, DBT, ADF, DAX, Power BI, Snowflake
  • AI/ML Integration: Experience integrating AI/ML models into data pipelines and analytics platforms.
  • Data Modeling: Hands-on experience in designing and implementing complex data models, with a strong understanding of normalization, denormalization, and schema designs such as star schema and snowflake schema.
  • Ingestion Processes: Hands-on experience in developing and optimizing EL (Extract and Load) processes using ADF (Azure Data Factory).
  • Data Transformation Processes: Hands-on experience in developing and optimizing DBT (Data Build Tool) models, including data testing.
  • Data Warehousing: Understanding of data warehousing concepts and best practices, particularly with the Snowflake platform, including optimization strategies, query tuning, and clustering.
  • Cloud Platforms: Experience with Azure, particularly in relation to data storage, integration, processing, and AI services.
  • Programming Languages: Proficiency in SQL and DAX; familiarity with Python or R for AI/ML tasks is a plus.
  • Visualization Expertise: Experience creating interactive and performant visualizations using Power BI, including designing and maintaining semantic models.
  • AI Training & Development: Experience working with the data, systems, and architecture to train and develop new AI-powered analytics and functionality.

Relevant Certifications

  • PL-300: Power BI Data Analyst Associate
  • DP-203: Azure Data Engineer Associate
  • SnowPro Core Certification
  • SnowPro Advanced: Data Analyst
  • SnowPro Advanced: Data Engineer (DEA-C02)
  • AI-102: Designing and Implementing an Azure AI Solution (Recommended)
  • MS Certified: Azure AI Engineer Associate (Optional but valuable)

Top 3 skill sets/technologies required for qualification:

  • 1): AI/ML
  • 2): Data Modeling
  • 3): Power BI

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.