Solution Architect
ADA
•
Seattle, WA
0
0
0
0
Not Applicable
Posted March 30, 2026
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Responsibilities
Commitments
Responsibilities
- Own end-to-end solution architecture for enterprise data platforms (lakehouse, warehouse, data mesh).
- Design cloud-agnostic and multi-cloud architectures across AWS, Azure, GCP, and hybrid environments.
- Define non-functional requirements: scalability, availability, security, performance, and cost efficiency.
- Produce architecture blueprints, reference designs, and technical standards.
- Data Engineering & Platforms
- Design and implement batch and streaming data pipelines (ETL/ELT).
- Architect data ingestion, storage, and consumption layers with clear data zoning and lifecycle management.
- Enable CI/CD, Infrastructure-as-Code, and automation for data platforms.
- Ensure high-quality, reliable, and well-documented data products.
- Analytics, AI & Agentic Solutions
- Enable analytics across the spectrum:
- Descriptive & diagnostic (BI, dashboards, reporting)
- Predictive & prescriptive (ML models, forecasting, optimization)
- Agentic analytics (LLM/RAG-based systems, autonomous or semi-autonomous agents)
- Architect platforms that support self-service analytics and experimentation.
- Define MLOps and model governance practices including deployment, monitoring, and retraining.
- Governance, Security & Operations
- Implement data governance, metadata management, lineage, and access controls.
- Ensure compliance with data privacy and regulatory requirements.
- Establish observability, SLOs, cost monitoring, and operational best practices.
- Leadership & Stakeholder Management
- Act as a technical leader and mentor for senior engineers and architects.
- Partner with product, analytics, and business teams to align data solutions with outcomes.
- Support client engagements, technical workshops, and solutioning where required.
Commitments
Unfortunately, we are only able to contact shortlisted applicants.
Not Met Priorities
What still needs stronger evidence
Requirements
- Experience: 10–15 years
- Predictive & prescriptive (ML models, forecasting, optimization)
- Agentic analytics (LLM/RAG-based systems, autonomous or semi-autonomous agents)
- 10+ years of experience across Data Engineering, Data Science, or Applied AI roles.
- Proven hands-on experience delivering end-to-end data and AI systems in production.
- Data Engineering
- Strong experience with modern data stacks (e.g., Spark, Databricks, Snowflake, BigQuery).
- Expertise in building reliable ETL/ELT pipelines and streaming architectures.
- Solid understanding of data modeling, governance, and data quality frameworks.
- Data Science & AI
- Experience across the full analytics spectrum: descriptive → agentic.
- Strong foundations in statistics, machine learning, and optimization.
- Hands-on experience with Python-based ML stacks.
- Generative & Agentic AI
- Practical experience building LLM-based systems using frameworks such as LangChain or similar.
- Experience with RAG, prompt engineering, tool/function calling, and agent orchestration.
- Understanding of AI safety, evaluation, and hallucination mitigation strategies.
- Strong problem-solving skills with a bias for execution.
- Comfortable working in ambiguity and shaping problems from first principles.
- Ability to balance speed, quality, and long-term architecture.
- Success Measures
- Delivery of a scalable, secure, cloud-agnostic data platform architecture.
- Reliable production-grade data pipelines and analytics enablement.
- Adoption of governance, automation, and operational best practices.
- Demonstrated business value through analytics, ML, or agentic use cases.
Preferred Skills
- Delivery of a scalable, secure, cloud-agnostic data platform architecture.
- Reliable production-grade data pipelines and analytics enablement.
About ADA
ADA is a leading data and artificial intelligence (AI) company that designs and executes integrated digital, analytics, and marketing solutions. We operate in 12 markets in Asia and partner with leading brands to drive their data and digital maturity
Solution Architect
Experience: 10–15 years
Employment Type: Full-time
About The Role
We are looking for a Solution Architect to design, build, and lead end-to-end data and analytics platforms. This role spans data engineering, analytics enablement, and advanced AI/agentic analytics. You will architect scalable, secure, and cloud-agnostic data solutions that support the full analytics spectrum—from descriptive and diagnostic analytics to predictive, prescriptive, and agent-driven systems.
You will work closely with business stakeholders, data engineers, analysts, and data scientists to translate business objectives into robust, future-ready data architectures.
Key Responsibilities Architecture & Strategy
Own end-to-end solution architecture for enterprise data platforms (lakehouse, warehouse, data mesh).
Design cloud-agnostic and multi-cloud architectures across AWS, Azure, GCP, and hybrid environments.
Define non-functional requirements: scalability, availability, security, performance, and cost efficiency.
Produce architecture blueprints, reference designs, and technical standards.
Data Engineering & Platforms
Design and implement batch and streaming data pipelines (ETL/ELT).
Architect data ingestion, storage, and consumption layers with clear data zoning and lifecycle management.
Enable CI/CD, Infrastructure-as-Code, and automation for data platforms.
Ensure high-quality, reliable, and well-documented data products.
Analytics, AI & Agentic Solutions
Enable analytics across the spectrum:
Descriptive & diagnostic (BI, dashboards, reporting)
Predictive & prescriptive (ML models, forecasting, optimization)
Agentic analytics (LLM/RAG-based systems, autonomous or semi-autonomous agents)
Architect platforms that support self-service analytics and experimentation.
Define MLOps and model governance practices including deployment, monitoring, and retraining.
Governance, Security & Operations
Implement data governance, metadata management, lineage, and access controls.
Ensure compliance with data privacy and regulatory requirements.
Establish observability, SLOs, cost monitoring, and operational best practices.
Leadership & Stakeholder Management
Act as a technical leader and mentor for senior engineers and architects.
Partner with product, analytics, and business teams to align data solutions with outcomes.
Support client engagements, technical workshops, and solutioning where required.
Must-Have Qualifications
Core Experience
10+ years of experience across Data Engineering, Data Science, or Applied AI roles.
Proven hands-on experience delivering end-to-end data and AI systems in production.
Data Engineering
Strong experience with modern data stacks (e.g., Spark, Databricks, Snowflake, BigQuery).
Expertise in building reliable ETL/ELT pipelines and streaming architectures.
Solid understanding of data modeling, governance, and data quality frameworks.
Data Science & AI
Experience across the full analytics spectrum: descriptive → agentic.
Strong foundations in statistics, machine learning, and optimization.
Hands-on experience with Python-based ML stacks.
Generative & Agentic AI
Practical experience building LLM-based systems using frameworks such as LangChain or similar.
Experience with RAG, prompt engineering, tool/function calling, and agent orchestration.
Understanding of AI safety, evaluation, and hallucination mitigation strategies.
Mindset
Strong problem-solving skills with a bias for execution.
Comfortable working in ambiguity and shaping problems from first principles.
Ability to balance speed, quality, and long-term architecture.
Success Measures
Delivery of a scalable, secure, cloud-agnostic data platform architecture.
Reliable production-grade data pipelines and analytics enablement.
Adoption of governance, automation, and operational best practices.
Demonstrated business value through analytics, ML, or agentic use cases.
Strong technical leadership and mentorship impact.
What We Offer
AI-first, client-facing delivery of data, AI, and reporting solutions across the full engagement lifecycle.
Hands-on work with modern stack including advanced analytics, ML, LLMs, RAG, and agentic systems applied to real business problems.
Cloud-agnostic architecture exposure across AWS, Azure, GCP, and hybrid environments.
High-impact role with visibility involving direct collaboration with senior client stakeholders and leadership.
Continuous learning & growth through certifications, knowledge sharing, and architectural ownership.
By submitting this, you agree to this Privacy Notice and you will be deemed to have consented to the collection, use, and disclosure of your Personal Information in accordance with this Privacy Notice: https://adaglobal.com/privacy-policy/
Unfortunately, we are only able to contact shortlisted applicants. We encourage you to continuously visit our website www.adaglobal.com for regular updates on available roles
We transform businesses using data, AI and tech | ADA
Pioneers in data and analytics, we are powering global marketing and commerce digital transformation with data and AI-led impact. Learn more here!
ADA is a leading data and artificial intelligence (AI) company that designs and executes integrated digital, analytics, and marketing solutions. We operate in 12 markets in Asia and partner with leading brands to drive their data and digital maturity
Solution Architect
Experience: 10–15 years
Employment Type: Full-time
About The Role
We are looking for a Solution Architect to design, build, and lead end-to-end data and analytics platforms. This role spans data engineering, analytics enablement, and advanced AI/agentic analytics. You will architect scalable, secure, and cloud-agnostic data solutions that support the full analytics spectrum—from descriptive and diagnostic analytics to predictive, prescriptive, and agent-driven systems.
You will work closely with business stakeholders, data engineers, analysts, and data scientists to translate business objectives into robust, future-ready data architectures.
Key Responsibilities Architecture & Strategy
Own end-to-end solution architecture for enterprise data platforms (lakehouse, warehouse, data mesh).
Design cloud-agnostic and multi-cloud architectures across AWS, Azure, GCP, and hybrid environments.
Define non-functional requirements: scalability, availability, security, performance, and cost efficiency.
Produce architecture blueprints, reference designs, and technical standards.
Data Engineering & Platforms
Design and implement batch and streaming data pipelines (ETL/ELT).
Architect data ingestion, storage, and consumption layers with clear data zoning and lifecycle management.
Enable CI/CD, Infrastructure-as-Code, and automation for data platforms.
Ensure high-quality, reliable, and well-documented data products.
Analytics, AI & Agentic Solutions
Enable analytics across the spectrum:
Descriptive & diagnostic (BI, dashboards, reporting)
Predictive & prescriptive (ML models, forecasting, optimization)
Agentic analytics (LLM/RAG-based systems, autonomous or semi-autonomous agents)
Architect platforms that support self-service analytics and experimentation.
Define MLOps and model governance practices including deployment, monitoring, and retraining.
Governance, Security & Operations
Implement data governance, metadata management, lineage, and access controls.
Ensure compliance with data privacy and regulatory requirements.
Establish observability, SLOs, cost monitoring, and operational best practices.
Leadership & Stakeholder Management
Act as a technical leader and mentor for senior engineers and architects.
Partner with product, analytics, and business teams to align data solutions with outcomes.
Support client engagements, technical workshops, and solutioning where required.
Must-Have Qualifications
Core Experience
10+ years of experience across Data Engineering, Data Science, or Applied AI roles.
Proven hands-on experience delivering end-to-end data and AI systems in production.
Data Engineering
Strong experience with modern data stacks (e.g., Spark, Databricks, Snowflake, BigQuery).
Expertise in building reliable ETL/ELT pipelines and streaming architectures.
Solid understanding of data modeling, governance, and data quality frameworks.
Data Science & AI
Experience across the full analytics spectrum: descriptive → agentic.
Strong foundations in statistics, machine learning, and optimization.
Hands-on experience with Python-based ML stacks.
Generative & Agentic AI
Practical experience building LLM-based systems using frameworks such as LangChain or similar.
Experience with RAG, prompt engineering, tool/function calling, and agent orchestration.
Understanding of AI safety, evaluation, and hallucination mitigation strategies.
Mindset
Strong problem-solving skills with a bias for execution.
Comfortable working in ambiguity and shaping problems from first principles.
Ability to balance speed, quality, and long-term architecture.
Success Measures
Delivery of a scalable, secure, cloud-agnostic data platform architecture.
Reliable production-grade data pipelines and analytics enablement.
Adoption of governance, automation, and operational best practices.
Demonstrated business value through analytics, ML, or agentic use cases.
Strong technical leadership and mentorship impact.
What We Offer
AI-first, client-facing delivery of data, AI, and reporting solutions across the full engagement lifecycle.
Hands-on work with modern stack including advanced analytics, ML, LLMs, RAG, and agentic systems applied to real business problems.
Cloud-agnostic architecture exposure across AWS, Azure, GCP, and hybrid environments.
High-impact role with visibility involving direct collaboration with senior client stakeholders and leadership.
Continuous learning & growth through certifications, knowledge sharing, and architectural ownership.
By submitting this, you agree to this Privacy Notice and you will be deemed to have consented to the collection, use, and disclosure of your Personal Information in accordance with this Privacy Notice: https://adaglobal.com/privacy-policy/
Unfortunately, we are only able to contact shortlisted applicants. We encourage you to continuously visit our website www.adaglobal.com for regular updates on available roles
We transform businesses using data, AI and tech | ADA
Pioneers in data and analytics, we are powering global marketing and commerce digital transformation with data and AI-led impact. Learn more here!