What are the responsibilities and job description for the "AI Data Engineer" position at Jobs via Dice?
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Job Title:- AI Data Engineer
Location:- Spring Texas (On-Site)
Job Type:- Long Term Contract
Need Only Local
W2 Role
Required: 10 Years Experience
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:
The biggest factor in our selection process is that the candidates demonstrate experience in their resumes engineering and implementing AI-ready data systems in Snowflake, transforming data with DBT, and visualizing it efficiently in Power BI, including implementing logic in DAX.
Job Title:- AI Data Engineer
Location:- Spring Texas (On-Site)
Job Type:- Long Term Contract
Need Only Local
W2 Role
Required: 10 Years Experience
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.
- 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.
- 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)
- 1): AI/ML
- 2): Data Modeling
- 3): Power BI
The biggest factor in our selection process is that the candidates demonstrate experience in their resumes engineering and implementing AI-ready data systems in Snowflake, transforming data with DBT, and visualizing it efficiently in Power BI, including implementing logic in DAX.
