

Data and AI Architect
β - Featured Role | Apply direct with Data Freelance Hub
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
-
ποΈ - Date discovered
September 16, 2025
π - Project duration
Unknown
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ποΈ - Location type
Unknown
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
Beverly Hills, CA
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π§ - Skills detailed
#Snowflake #Model Deployment #Data Security #Deployment #Security #Data Strategy #Data Architecture #GDPR (General Data Protection Regulation) #Spark (Apache Spark) #Data Pipeline #BigQuery #Base #Cloud #Data Science #Strategy #IoT (Internet of Things) #Automation #Data Lake #GCP (Google Cloud Platform) #Data Integration #Data Quality #"ETL (Extract #Transform #Load)" #Data Management #Computer Science #AI (Artificial Intelligence) #ML (Machine Learning) #Data Governance #Consulting #Databricks #Synapse #AWS SageMaker #Kafka (Apache Kafka) #Metadata #Cybersecurity #NLP (Natural Language Processing) #Leadership #Monitoring #Scala #AWS (Amazon Web Services) #Data Engineering #SageMaker #Compliance #Redshift #Azure
Role description
We are looking for a Data & AI Architect to design and lead the development of data-driven and AI-enabled solutions. This role will be responsible for shaping enterprise data strategy, modernizing data platforms, and implementing AI/ML capabilities that enable innovation, automation, and business value. The ideal candidate combines expertise in data architecture, cloud platforms, and applied AI with strong business acumen and leadership skills.
Responsibilities
β’ Data Architecture & Strategy
β’ Define enterprise data architecture, including data lakes, warehouses, and streaming platforms.
β’ Establish data governance frameworks, metadata management, and data quality standards.
β’ Align data strategy with organizational goals and digital transformation initiatives.
β’ AI/ML Solution Design
β’ Architect and oversee the implementation of AI/ML solutions for predictive analytics, personalization, automation, and decision support.
β’ Partner with data science teams to operationalize models at scale.
β’ Select and integrate AI frameworks, MLOps tools, and cloud-native AI services.
β’ Platform Engineering & Integration
β’ Design and manage cloud-based data platforms (AWS, Azure, GCP).
β’ Define data pipelines, APIs, and real-time data integration patterns.
β’ Ensure scalability, performance, and security across platforms.
β’ Governance & Compliance
β’ Ensure AI/ML solutions comply with ethical AI guidelines, privacy regulations (GDPR, CCPA), and enterprise security standards.
β’ Establish monitoring and audit mechanisms for AI systems to ensure transparency and accountability.
β’ Collaboration & Leadership
β’ Act as a strategic advisor to business and technology leaders on data and AI opportunities.
β’ Collaborate with stakeholders across IT, data science, product, and business units.
β’ Mentor engineers, data scientists, and analysts in best practices for data and AI architecture.
Required
β’ 8+ years of experience in data architecture, enterprise data management, or AI/ML solution design.
β’ Proven expertise with modern data platforms (Databricks, Snowflake, BigQuery, Synapse, Redshift, etc.).
β’ Strong experience with cloud services (AWS SageMaker, Azure ML, GCP Vertex AI, etc.).
β’ Proficiency in data integration, APIs, and streaming technologies (Kafka, Spark, Flink).
β’ Solid understanding of AI/ML lifecycle, MLOps, and model deployment.
β’ Knowledge of data security, compliance, and ethical AI practices.
β’ Excellent communication and stakeholder engagement skills.
Preferred Qualifications
β’ Advanced degree in Computer Science, Data Science, or related field.
β’ Certification in cloud platforms (AWS Solutions Architect, Azure Data Engineer, GCP Data Engineer).
β’ Experience in both structured and unstructured data domains (IoT, NLP, computer vision).
β’ Background in both B2B and B2C data-driven solutions.
β’ Experience working in consulting or multi-client environments.
Success Measures
β’ Implementation of a scalable, secure, and future-ready data and AI architecture.
β’ Increased business value from AI-driven insights, automation, and innovation.
β’ Strong adoption of data and AI capabilities across the organization.
β’ Demonstrated improvement in data quality, accessibility, and trust.
Benefits
β’ 401(k).
β’ Dental Insurance.
β’ Health insurance.
β’ Vision insurance.
β’ We are an equal-opportunity employer and value diversity, equality, inclusion, and respect for people.
β’ The salary will be determined based on several factors, including, but not limited to, location, relevant education, qualifications, experience, technical skills, and business needs.
Additional Responsibilities
β’ Participate in OP monthly team meetings and participate in team-building efforts.
β’ Contribute to OP technical discussions, peer reviews, etc.
β’ Contribute content and collaborate via the OP-Wiki/Knowledge Base.
β’ Provide status reports to OP Account Management as requested.
About Us
OP is a technology consulting and solutions company, offering advisory and managed services, innovative platforms, and staffing solutions across a wide range of fields β including AI, cybersecurity, enterprise architecture, and beyond. Our most valuable asset is our people: dynamic, creative thinkers who are passionate about doing quality work. As a member of the OP team, you will have access to industry-leading consulting practices, strategies & and technologies, innovative training & education. An ideal OP team member is a technology leader with a proven track record of technical excellence and a strong focus on process and methodology.
We are looking for a Data & AI Architect to design and lead the development of data-driven and AI-enabled solutions. This role will be responsible for shaping enterprise data strategy, modernizing data platforms, and implementing AI/ML capabilities that enable innovation, automation, and business value. The ideal candidate combines expertise in data architecture, cloud platforms, and applied AI with strong business acumen and leadership skills.
Responsibilities
β’ Data Architecture & Strategy
β’ Define enterprise data architecture, including data lakes, warehouses, and streaming platforms.
β’ Establish data governance frameworks, metadata management, and data quality standards.
β’ Align data strategy with organizational goals and digital transformation initiatives.
β’ AI/ML Solution Design
β’ Architect and oversee the implementation of AI/ML solutions for predictive analytics, personalization, automation, and decision support.
β’ Partner with data science teams to operationalize models at scale.
β’ Select and integrate AI frameworks, MLOps tools, and cloud-native AI services.
β’ Platform Engineering & Integration
β’ Design and manage cloud-based data platforms (AWS, Azure, GCP).
β’ Define data pipelines, APIs, and real-time data integration patterns.
β’ Ensure scalability, performance, and security across platforms.
β’ Governance & Compliance
β’ Ensure AI/ML solutions comply with ethical AI guidelines, privacy regulations (GDPR, CCPA), and enterprise security standards.
β’ Establish monitoring and audit mechanisms for AI systems to ensure transparency and accountability.
β’ Collaboration & Leadership
β’ Act as a strategic advisor to business and technology leaders on data and AI opportunities.
β’ Collaborate with stakeholders across IT, data science, product, and business units.
β’ Mentor engineers, data scientists, and analysts in best practices for data and AI architecture.
Required
β’ 8+ years of experience in data architecture, enterprise data management, or AI/ML solution design.
β’ Proven expertise with modern data platforms (Databricks, Snowflake, BigQuery, Synapse, Redshift, etc.).
β’ Strong experience with cloud services (AWS SageMaker, Azure ML, GCP Vertex AI, etc.).
β’ Proficiency in data integration, APIs, and streaming technologies (Kafka, Spark, Flink).
β’ Solid understanding of AI/ML lifecycle, MLOps, and model deployment.
β’ Knowledge of data security, compliance, and ethical AI practices.
β’ Excellent communication and stakeholder engagement skills.
Preferred Qualifications
β’ Advanced degree in Computer Science, Data Science, or related field.
β’ Certification in cloud platforms (AWS Solutions Architect, Azure Data Engineer, GCP Data Engineer).
β’ Experience in both structured and unstructured data domains (IoT, NLP, computer vision).
β’ Background in both B2B and B2C data-driven solutions.
β’ Experience working in consulting or multi-client environments.
Success Measures
β’ Implementation of a scalable, secure, and future-ready data and AI architecture.
β’ Increased business value from AI-driven insights, automation, and innovation.
β’ Strong adoption of data and AI capabilities across the organization.
β’ Demonstrated improvement in data quality, accessibility, and trust.
Benefits
β’ 401(k).
β’ Dental Insurance.
β’ Health insurance.
β’ Vision insurance.
β’ We are an equal-opportunity employer and value diversity, equality, inclusion, and respect for people.
β’ The salary will be determined based on several factors, including, but not limited to, location, relevant education, qualifications, experience, technical skills, and business needs.
Additional Responsibilities
β’ Participate in OP monthly team meetings and participate in team-building efforts.
β’ Contribute to OP technical discussions, peer reviews, etc.
β’ Contribute content and collaborate via the OP-Wiki/Knowledge Base.
β’ Provide status reports to OP Account Management as requested.
About Us
OP is a technology consulting and solutions company, offering advisory and managed services, innovative platforms, and staffing solutions across a wide range of fields β including AI, cybersecurity, enterprise architecture, and beyond. Our most valuable asset is our people: dynamic, creative thinkers who are passionate about doing quality work. As a member of the OP team, you will have access to industry-leading consulting practices, strategies & and technologies, innovative training & education. An ideal OP team member is a technology leader with a proven track record of technical excellence and a strong focus on process and methodology.