ML Cost Optimization EngineerOpenkyber • TX, United States

ML Cost Optimization Engineer

Openkyber • TX, United States

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Role : AI Data Engineer- Expert Level

Location : Spring TX (5 days onsite)

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 designing and implementing complex data models, with strong understanding of normalization, denormalization, and schema designs such as star and snowflake schema.

Ingestion Processes : Hands-on experience developing and optimizing EL (Extract and Load) processes using ADF (Azure Data Factory).

Data Transformation Processes : Hands-on experience developing and optimizing DBT (Data Build Tool) models, including data testing.

Data Warehousing : Understanding of data warehousing concepts and best practices, particularly with 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 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)

Microsoft Certified : Azure AI Engineer Associate (Optional but valuable)

Top 3 skill sets / technologies required for qualification :

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