Senior Solution Architect

Tiger Analytics, LLC; Dallas (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

Tiger Analytics is seeking a highly experienced Senior Data & Analytics Solution Architect to lead enterprise-scale modernization and digital transformation initiatives. The role focuses on AWS and Databricks, with deep expertise in data platforms and engagement with CXO-level stakeholders.

The candidate will guide architecture workshops, design scalable data solutions, and drive governance, security, and modernization across cloud data platforms in a global consulting environment.

Qualifications

• 18+ years IT experience with at least 10 years in Enterprise Data & Analytics Architecture.
• Strong expertise in AWS Cloud services including S3, Glue, EMR, Lambda, Redshift, Athena, IAM, Lake Formation, Step Functions, CloudWatch, EventBridge, ECS/EKS.
• Extensive hands-on experience with Databricks, Delta Lake, Unity Catalog, Spark, PySpark, and Lakehouse architecture.
• Strong understanding of enterprise Data Warehouse, Data Lake, and Lakehouse architectures.
• Expertise in modern data engineering, ETL/ELT, metadata management, data governance, and master data management.
• Strong knowledge of SQL, distributed data processing, cloud-native architecture patterns, and scalable data platform design.
• Experience designing enterprise integration architectures using APIs, streaming technologies, messaging systems, and event-driven architectures.
• Deep understanding of cloud migration strategies, modernization approaches, and hybrid architecture patterns.
• Strong stakeholder management with proven experience interacting directly with executive leadership.
• Excellent consulting, advisory, presentation, and communication skills.

Responsibilities

• Lead enterprise Data & Analytics architecture engagements, designing scalable, secure, and future-ready solutions using AWS and Databricks aligned with business objectives.
• Assess existing legacy data ecosystems and define target-state architecture, modernization roadmaps, migration strategies, and technology blueprints for enterprise transformation programs.
• Act as a trusted advisor to senior client stakeholders (CXO, VP, Director level), conducting architecture workshops, technical discovery sessions, and strategic consulting engagements.
• Drive end-to-end solution architecture across cloud data platforms, including data lakes, lakehouses, enterprise data warehouses, streaming platforms, metadata management, governance, and analytics ecosystems.
• Define enterprise architecture standards, reusable design patterns, best practices, and governance frameworks while ensuring alignment with organizational technology strategies.
• Lead technical solutioning discussions involving clients, implementation partners, and cross-functional delivery teams to ensure architecture consistency and successful program execution.
• Design scalable data ingestion, transformation, storage, and analytics architectures supporting structured, semi-structured, and unstructured data.
• Collaborate closely with business, product, engineering, and data science teams to translate business requirements into scalable technical solutions.
• Recommend platform accelerators, reusable frameworks, automation opportunities, and optimization strategies to improve delivery efficiency and reduce implementation timelines.
• Provide architectural oversight throughout project execution, reviewing technical designs, resolving complex technical challenges, and mentoring global engineering teams.
• Lead architecture governance by conducting solution reviews, ensuring compliance with enterprise security, scalability, performance, and data governance standards.
• Drive cloud modernization initiatives involving migration from legacy data platforms to AWS-based cloud-native architectures.
• Evaluate emerging technologies and recommend innovative solutions across Data Engineering, AI/ML, GenAI, and cloud ecosystems.
• Support proposal development, solution estimations, RFP responses, technical presentations, and executive-level client discussions.

Skills

Cloud architecture

Executive stakeholder mgmt

Data & Analytics Architecture

Solution architecture

AWS Cloud

Databricks

SQL

Leadership

Tools

AWS services (S3, Glue, EMR, Lambda, Redshift, Athena, IAM, Lake Formation, Step Functions, CloudWatch, EventBridge, ECS/EKS)

Databricks

Delta Lake

Unity Catalog

Spark / PySpark

Lakehouse architecture

Job description

Tiger Analytics is a global leader in AI and advanced analytics consulting, empowering Fortune 1000 companies to solve their toughest business challenges. We are on a mission to push the boundaries of what AI can do, providing data-driven certainty for a better tomorrow. Our diverse team of over 6,000 technologists and consultants operates across five continents, building cutting-edge ML and data solutions at scale. Join us to do great work and shape the future of enterprise AI.

Tiger Analytics is looking for a highly experienced Senior Data & Analytics Solution Architect to lead enterprise-scale modernization and digital transformation initiatives. The ideal candidate will have deep expertise in AWS and Databricks, extensive experience designing enterprise data platforms, and the ability to engage with CXO-level stakeholders to define future-state architectures. This role requires strong consulting, advisory, and technical leadership skills to drive large-scale Data & AI transformation programs.

Key Responsibilities

• Lead enterprise Data & Analytics architecture engagements, designing scalable, secure, and future-ready solutions using AWS and Databricks aligned with business objectives.
• Assess existing legacy data ecosystems and define target-state architecture, modernization roadmaps, migration strategies, and technology blueprints for enterprise transformation programs.
• Act as a trusted advisor to senior client stakeholders (CXO, VP, Director level), conducting architecture workshops, technical discovery sessions, and strategic consulting engagements.
• Drive end-to-end solution architecture across cloud data platforms, including data lakes, lakehouses, enterprise data warehouses, streaming platforms, metadata management, governance, and analytics ecosystems.
• Define enterprise architecture standards, reusable design patterns, best practices, and governance frameworks while ensuring alignment with organizational technology strategies.
• Lead technical solutioning discussions involving clients, implementation partners, and cross-functional delivery teams to ensure architecture consistency and successful program execution.
• Design scalable data ingestion, transformation, storage, and analytics architectures supporting structured, semi-structured, and unstructured data.
• Collaborate closely with business, product, engineering, and data science teams to translate business requirements into scalable technical solutions.
• Recommend platform accelerators, reusable frameworks, automation opportunities, and optimization strategies to improve delivery efficiency and reduce implementation timelines.
• Provide architectural oversight throughout project execution, reviewing technical designs, resolving complex technical challenges, and mentoring global engineering teams.
• Lead architecture governance by conducting solution reviews, ensuring compliance with enterprise security, scalability, performance, and data governance standards.
• Drive cloud modernization initiatives involving migration from legacy data platforms to AWS-based cloud-native architectures.
• Evaluate emerging technologies and recommend innovative solutions across Data Engineering, AI/ML, GenAI, and cloud ecosystems.
• Support proposal development, solution estimations, RFP responses, technical presentations, and executive-level client discussions.

• 18+ years of IT experience with at least 10 years in Enterprise Data & Analytics Architecture.
• Strong expertise in AWS Cloud services including S3, Glue, EMR, Lambda, Redshift, Athena, IAM, Lake Formation, Step Functions, CloudWatch, EventBridge, ECS/EKS, and related services.
• Extensive hands-on experience with Databricks, Delta Lake, Unity Catalog, Spark, PySpark, and Lakehouse architecture.
• Strong understanding of enterprise Data Warehouse, Data Lake, and Lakehouse architectures.
• Expertise in modern data engineering principles, ETL/ELT frameworks, metadata management, data governance, and master data management.
• Strong knowledge of SQL, distributed data processing, cloud-native architecture patterns, and scalable data platform design.
• Experience designing enterprise integration architectures using APIs, streaming technologies, messaging systems, and event-driven architectures.
• Deep understanding of cloud migration strategies, modernization approaches, and hybrid architecture patterns.
• Strong stakeholder management with proven experience interacting directly with executive leadership.
• Excellent consulting, advisory, presentation, and communication skills.

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.