Data Architect

Akkodis is seeking a Data Architect for a Direct Hire (FTE) position, and this is a 100% Remote role. Ideally the client is looking for applicants with a solid background in AI, Data Architecture, Data Warehouse, Python, and Snowflake.

Salary Range: $160K - $185K annually. The rate may be negotiable based on experience, education, geographic location, and other factors.

WHAT YOU’LL DO:

• Data and AI Architecture Leadership: Design and implement advanced data platforms and AI architecture, enabling enterprise-scale analytics, machine learning, and intelligent automation across the division.
• Strategy & Planning: Collaborate with enterprise architects and business stakeholders to define a vision and roadmap for data modernization, MLOps, and AI governance aligned to strategic outcomes.
• AI Innovation & Prototyping: Lead the development of AI models, POCs, and pipelines using cutting-edge technologies. Explore "what-if" scenarios, whiteboarding, and design sprints to evaluate new opportunities and validate business impact.
• Governance & Ethics: Establish and uphold standards for data quality, stewardship, ethical AI practices, and secure model deployment while promoting regulatory compliance and trust.
• Mentorship & Enablement: Coach engineers and analysts in data modeling, feature engineering, and ML development. Promote knowledge sharing and establish best practices across data science and data engineering teams.
• Collaboration & Integration: Integrate data solutions with microservices, event-based architectures, and external business partners, ensuring scalability, observability, and operational readiness.

WHAT YOU’LL BRING:

• 5+ years of experience in leading data architecture initiatives, including cloud-native data platforms, machine learning lifecycle management, and enterprise data integration.

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• Expertise in distributed data systems, data warehouse, data Lakehouse architecture, and model operationalization frameworks such as MLflow, Sagemaker, or similar.
• Proficiency in Python, SQL, Snowflake and MongoDB and cloud technologies (AWS preferred), with experience deploying ML models using containers, APIs, or serverless frameworks.
• Proficiency in logical and physical data modeling, multidimensional modeling, normalization and denormalization techniques.
• Experience in building data systems in microservice environments that provide access to data for operational and analytical needs (BI/ML/AI).
• Experience translating business strategies into data solutions with measurable outcomes.
• Proficiency in design and development of ETL/ELT methodologies from source to target supporting data processing and transformations to deliver data-driven business insights and decisions.
• Strong understanding of data governance, explainability, and responsible data principles.
• Familiarity with data observability tools, CI/CD for ML, and lineage/trust frameworks.
• Comfortable working in agile environments and guiding architecture for Agile Release Trains (ART).
• Excellent communication, stakeholder engagement, and cross-functional leadership skills.

PREFERRED:

• TOGAF Certified.
• Group Benefits or insurance industry experience.

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• Experience with MongoDB, Snowflake, AWS AI/ML stack (SageMaker, Glue, Redshift, Bedrock, etc.).
• Familiarity with MLOps, data mesh principles, and real-time analytics (Kafka, Spark).
• Artificial Intelligence experience is preferred but not required. A strong willingness to learn and grow in AI technologies is highly valued.

If you are interested in this role, then please click APPLY NOW. For other opportunities available at Akkodis, or any questions, please contact Narendra Pratap at (213)-410-5211 or narendra.pratap@akkodis.com.

Equal Opportunity Employer/Veterans/Disabled

Benefits offerings include but are not limited to:

401(k) with match

Medical insurance

Dental Insurance

Vision assistance

Paid Holidays Off

To read our Candidate Privacy Information Statement, which explains how we will use your information, please visit https://www.akkodis.com/en/privacy-policy.