Data Architect (Data Modernization)
OverviewWe are seeking an experienced Data Architect to lead the technical architecture work stream of a comprehensive Data Modernization Assessment for our client. This role is instrumental in defining the future-state architecture across infrastructure, data pipelines, governance frameworks, and analytics platforms. The ideal candidate has deep expertise in enterprise data architecture, modern cloud data platforms, and designing scalable, AI-ready data ecosystems. Job Responsibilities
Assess and document the current enterprise data architecture, including ingestion, processing, storage, and consumption layers across cloud and hybrid systems.
Lead the review of data pipelines and infrastructure, identifying opportunities to optimize scalability, reliability, performance, and cost-efficiency.
Design and recommend target-state architecture aligned to modernization objectives, including support for data products, domain ownership models, and AI-readiness.
Evaluate and improve monitoring, observability, and lineage capabilities, ensuring system transparency and operational resilience.
Guide the design and enhancement of metadata and governance frameworks, including cataloging, data stewardship, access control, and compliance alignment.
Collaborate with cross-functional teams to assess and integrate the existing analytics tooling landscape into the broader architecture vision.
Provide architectural guidance to support agentic BI and AI-driven analytics initiatives, ensuring foundational readiness across data layers.
Translate assessment findings into strategic architecture roadmaps and reference models, enabling phased modernization.
Partner with the Technical Product Manager and Engineering leads to align architecture with business goals and operational realities. Basic Qualifications
5 - 7 years of experience in data architecture or enterprise architecture roles, with a strong foundation in designing and modernizing large-scale data systems.
Proven experience architecting solutions on cloud platforms such as AWS, Azure, or GCP using modern components (e.g., Lakehouse, Delta Lake, Redshift, BigQuery, Snowflake, etc.).
Expertise in data modeling, data integration frameworks, and real-time/batch processing architecture (e.g., Spark, Kafka, dbt, etc.).
Solid understanding of data governance, metadata management, and security practices, including experience with tools like Collibra, Alation, or AWS Glue Data Catalog.
Familiarity with observability frameworks, system health monitoring, and end-to-end data lineage design.
Experience evaluating or designing support for advanced analytics, AI/ML pipelines, and agentic BI solutions.
Strong communication and stakeholder engagement skills, capable of working with executives, engineers, and analysts to bridge business and technical needs. Preferred Qualifications
Experience working in regulated enterprise environments (e.g., finance, healthcare, energy).
Exposure to agentic AI systems, LLM integrations, or modern autonomous analytics platforms.
Certifications in cloud architecture (e.g., AWS Certified Data Analytics – Specialty, Azure Data Engineer Associate, Google Professional Data Engineer). Additional Information
We are proud to offer a competitive salary alongside a strong healthcare insurance and benefits package. The role is preferably hybrid, with 2 days per week spent in the office, and flexibility for client engagement needs. We pride ourselves on the growth of our employees, offering extensive learning and development resources.
ShyftLabs is an equal-opportunity employer committed to creating a safe, diverse and inclusive environment. We encourage qualified applicants of all backgrounds including ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, nationality, and education levels to apply. If you are contacted for an interview and require accommodation during the interviewing process, please let us know.
Apply Now
Assess and document the current enterprise data architecture, including ingestion, processing, storage, and consumption layers across cloud and hybrid systems.
Lead the review of data pipelines and infrastructure, identifying opportunities to optimize scalability, reliability, performance, and cost-efficiency.
Design and recommend target-state architecture aligned to modernization objectives, including support for data products, domain ownership models, and AI-readiness.
Evaluate and improve monitoring, observability, and lineage capabilities, ensuring system transparency and operational resilience.
Guide the design and enhancement of metadata and governance frameworks, including cataloging, data stewardship, access control, and compliance alignment.
Collaborate with cross-functional teams to assess and integrate the existing analytics tooling landscape into the broader architecture vision.
Provide architectural guidance to support agentic BI and AI-driven analytics initiatives, ensuring foundational readiness across data layers.
Translate assessment findings into strategic architecture roadmaps and reference models, enabling phased modernization.
Partner with the Technical Product Manager and Engineering leads to align architecture with business goals and operational realities. Basic Qualifications
5 - 7 years of experience in data architecture or enterprise architecture roles, with a strong foundation in designing and modernizing large-scale data systems.
Proven experience architecting solutions on cloud platforms such as AWS, Azure, or GCP using modern components (e.g., Lakehouse, Delta Lake, Redshift, BigQuery, Snowflake, etc.).
Expertise in data modeling, data integration frameworks, and real-time/batch processing architecture (e.g., Spark, Kafka, dbt, etc.).
Solid understanding of data governance, metadata management, and security practices, including experience with tools like Collibra, Alation, or AWS Glue Data Catalog.
Familiarity with observability frameworks, system health monitoring, and end-to-end data lineage design.
Experience evaluating or designing support for advanced analytics, AI/ML pipelines, and agentic BI solutions.
Strong communication and stakeholder engagement skills, capable of working with executives, engineers, and analysts to bridge business and technical needs. Preferred Qualifications
Experience working in regulated enterprise environments (e.g., finance, healthcare, energy).
Exposure to agentic AI systems, LLM integrations, or modern autonomous analytics platforms.
Certifications in cloud architecture (e.g., AWS Certified Data Analytics – Specialty, Azure Data Engineer Associate, Google Professional Data Engineer). Additional Information
We are proud to offer a competitive salary alongside a strong healthcare insurance and benefits package. The role is preferably hybrid, with 2 days per week spent in the office, and flexibility for client engagement needs. We pride ourselves on the growth of our employees, offering extensive learning and development resources.
ShyftLabs is an equal-opportunity employer committed to creating a safe, diverse and inclusive environment. We encourage qualified applicants of all backgrounds including ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, nationality, and education levels to apply. If you are contacted for an interview and require accommodation during the interviewing process, please let us know.
Apply Now