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Commission Snowflake Jobs in Arizona (NOW HIRING)

Data Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

Knowledge of Snowflake, DBT, and cloud-native analytics platforms preferred * Strong problem ... This job is not eligible for bonuses, incentives or commissions. Kforce is an Equal Opportunity ...

Commission Snowflake information

What is a commission snowflake?

Commission Snowflake jobs typically refer to roles that involve working with Snowflake, a cloud-based data warehousing platform, where compensation is partially or fully based on commission or performance metrics. These positions are common in sales, customer success, or partner management, where employees earn commissions for selling or promoting Snowflake solutions. Responsibilities may include identifying new business opportunities, managing client relationships, and meeting predefined sales targets. Success in these roles often requires a strong understanding of data warehousing, cloud technologies, and excellent communication skills.

What are the key skills and qualifications needed to thrive as a Snowflake data engineer, and why are they important?

To thrive as a Snowflake Data Engineer, you need strong skills in SQL, data warehousing concepts, and experience with Snowflake's cloud data platform, typically supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud platforms like AWS or Azure, and Snowflake certifications are highly valued. Problem-solving, analytical thinking, and effective communication are crucial soft skills for success in this role. These competencies ensure efficient data management, seamless integration, and valuable insights for data-driven decision-making.

What are some common challenges faced by professionals in commissioning roles for Snowflake implementations?

Professionals overseeing the commissioning of Snowflake implementations often face challenges such as integrating Snowflake with existing data ecosystems, ensuring data security and compliance, and optimizing performance for diverse workloads. Effective collaboration with IT, data engineering, and business teams is crucial to align requirements and troubleshoot integration issues. Staying updated on Snowflake's evolving features and best practices also helps in overcoming technical hurdles and delivering successful deployments.

What is the difference between Commission Snowflake vs Commission Analyst?

AspectCommission SnowflakeCommission Analyst
CredentialsTypically requires knowledge of Snowflake platform, data analysis, and sales commission systemsRequires understanding of sales data, commission calculations, and reporting tools
Work EnvironmentData-driven, technical environment focused on Snowflake data platformFinancial and sales-focused environment analyzing commission data
Employer & IndustryTech companies, data analytics firms, sales organizations using SnowflakeSales departments, finance teams, and compensation analysis units

While both roles involve commissions, a Commission Snowflake specializes in managing and analyzing commissions within the Snowflake data platform, whereas a Commission Analyst focuses on calculating and reporting sales commissions across various systems. The roles overlap in data analysis and sales compensation but differ in technical focus and platform expertise.

What are the most commonly searched types of Snowflake jobs in Arizona? The most popular types of Snowflake jobs in Arizona are:
What cities in Arizona are hiring for Commission Snowflake jobs? Cities in Arizona with the most Commission Snowflake job openings:

Machine Learning Operations (MLOps) Engineer

Kforce Technology Staffing

Phoenix, AZ • On-site

$101K - $134K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 8 days ago


Job description

RESPONSIBILITIES:
Kforce has a client that is seeking a Machine Learning Operations (MLOps) Engineer (Snowflake) in Phoenix, AZ.
Summary:
We are seeking a Senior MLOps Engineer to help design and build an enterprise-scale machine learning platform from the ground up. This is a unique opportunity to establish a modern MLOps ecosystem on Snowflake, supporting end-to-end model development, deployment, and lifecycle management.
The platform will be built on a medallion architecture (Bronze, Silver, Gold), enabling machine learning models to consume trusted, governed data products with full lineage, scalability, and performance. This role will play a key part in shaping standards, processes, and tooling as the platform evolves from MVP to enterprise scale.
Key Responsibilities:
* Architect and build a production-grade MLOps platform on Snowflake, leveraging Snowpark, Snowflake ML, Model Registry, and Feature Store
* Design and operationalize reusable pipelines for training, validation, deployment, inference, and monitoring
* Align ML workflows with Bronze, Silver, and Gold medallion layers to ensure consistent use of trusted data
* Establish model lifecycle management standards, including versioning, approvals, promotion gates, and rollback strategies
* Partner with data scientists to productionize models into scalable, reliable services
* Implement model observability for performance, drift, bias, and data quality, with alerting and SLOs
* Automate retraining and refresh processes using Snowflake Tasks, Dynamic Tables, and event-driven orchestration
* Collaborate with data engineering teams to ensure reliable and reusable feature pipelines
* Define and implement CI/CD pipelines for ML systems, including testing frameworks and release controls
* Drive governance across security, compliance, auditability, reproducibility, and responsible AI practices
* Lead platform maturation, including documentation, developer enablement, and operational runbooks
REQUIREMENTS:
* 5+ years of experience in ML Engineering, MLOps, or platform engineering
* Strong Python and SQL skills, with experience building production ML pipelines
* Hands-on experience with Snowflake data platforms (Snowpark and Snowflake ML strongly preferred)
* Experience with model deployment, versioning, monitoring, and lifecycle governance
* Experience implementing CI/CD and testing strategies for ML systems
* Strong understanding of feature engineering, training-serving consistency, and data quality controls
* Experience working with cloud platforms (AWS preferred)
* Proven ability to collaborate across data science, data engineering, and business teams
Preferred Qualifications:
* Experience with Snowflake Model Registry and Feature Store
* Background in medallion/lakehouse data architectures
* Experience with dbt or similar transformation tools
* Familiarity with streaming or near real-time ML inference
* Experience in high-volume operational environments (e.g., logistics, fleet, routing)
* Prior experience building greenfield platforms and establishing standards from scratch
This role can be performed fully remotely but there is a preference for Phoenix local talent. This role has the potential to convert to FTE with Kforce's client.
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
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