Enterprise Data Architect

BayOne Solutions; San Francisco (CA); Hybrid; USD 144,000 - 201,000; Full time

Job summary

A leading company is seeking an Enterprise Data and AI/ML Architect for a hybrid role in San Francisco. In this position, you will design scalable data architectures and oversee ML solutions across various systems including Ecommerce and digital marketing. Candidates should have strong backgrounds in ML-Ops and data engineering practices, along with experience using Azure DataBricks and Dataiku.

Qualifications

• Mid-senior level experience required.
• Prior experience with Azure DataBricks, Dataiku, and cloud databases preferred.
• Strong understanding of ML-Ops and data engineering practices.

Responsibilities

• Lead the architecture and design of business initiatives related to data platforms.
• Design and oversee pipelines for data ingestion and transformation.
• Translate business problems to machine learning solutions.

Skills

Machine Learning Operations

Data Engineering

Feature Engineering

Data Democratization

Data Mesh Approach

Education

Degree in Computer Science or related field

Tools

Azure DataBricks

Dataiku

Job description

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This range is provided by BayOne Solutions. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$80.00/hr - $90.00/hr

Position: Enterprise Data and AI/ML Architect

Position Type: Contract to Hire

Remote Eligible: Hybrid Schedule, Near Shore Acceptable

Your role:

As an Enterprise Data and AI/ML Architect, you will be responsible to lead the architecture and design of Data Platform and leverage it for AI/ML solutions. Reporting to the Director, Architecture you will:

• Lead the Architecture and design of business and tech initiatives related to Data Platforms and its use in AI/ML across different systems and applications including Ecommerce (Search, Browse, Cart, Checkout), Web/Mobile, Digital Marketing and Retail Systems.

• Design and oversee pipelines for data ingestion, transformation, and feature engineering.

• Define scalable data & AI/ML architecture across structured, semi-structured and unstructured Data Sources.

• Work with engineering teams to translate business problems to ML solutions. Help guide development and curation of ML models from experimentation to production deployments.

• Good knowledge and prior practice of ML-Ops, model deployments, monitoring and version control.

• Good knowledge of organizational practices in Data engineering including Data democratization, Data Mesh approaches and creation of Data Products.

• Ideal candidate will have prior experience with Azure DataBricks, Dataiku and cloud database technologies.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Job function

  Information Technology

• Industries

  Retail

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