Data Solution Architect

Job Title: Data Solution ArchitectLocation: Fosters City, CA (Onsite)Job Type: FTEJob Description:Primary (Must Have) Skills10+ years of experience in Data Engineering, Data Integration, or Data Platform delivery.Strong hands-on experience with Databricks on AWS.Expertise in Apache Spark, PySpark, Delta Lake, and Lakehouse architecture.Experience designing and implementing enterprise-scale data pipelines.Strong understanding of AWS services such as S3, Glue, Lambda, Redshift, IAM, and CloudWatch.Hands-on experience with MDM implementations and integrations.Experience with data quality, data governance, lineage, and master data management processes.Strong experience integrating enterprise systems using middleware platforms such as MuleSoft, Boomi, Kafka, or API-based integrations.Experience working with structured, semi-structured, and unstructured datasets.Strong SQL and Python development skills.Experience with Agile delivery methodologies and DevOps practices.Experience leading distributed teams and managing stakeholder communications.Secondary Skills (Good to Have)Experience with Snowflake or Microsoft Fabric.Exposure to AI/ML enablement using Databricks ML or AWS SageMaker.Experience with Unity Catalog and data governance frameworks.Knowledge of Data Mesh and Data Product concepts.Experience with real-time streaming using Kafka or Kinesis.Experience with Informatica IDMC, Talend, or Azure Data Factory.Knowledge of Healthcare, life sciences, retail, manufacturing, or financial services domains.Exposure to GenAI and enterprise AI adoption initiatives.Role SummaryClient is seeking a seasoned Data Engineering Lead with strong expertise in Databricks on AWS, MDM, and enterprise data integration.The candidate will lead the design and delivery of modern data platforms that enable trusted, governed, and scalable data consumption across business functions.This role requires deep experience in cloud-based data engineering, middleware integrations, data governance, and enterprise-scale analytics solutions.The ideal candidate will work closely with business, architecture, analytics, and engineering teams to drive data modernization initiatives.Why This Role MattersThis role will be instrumental in enabling the client's enterprise data modernization journey.The individual will help establish a scalable and governed data foundation that supports advanced analytics, AI/ML initiatives, and business decision-making.Success in this role will directly improve data quality, consistency, and accessibility across critical business domains.What You'll DoLead the design and implementation of Databricks-based data platforms on AWS.Architect scalable Lakehouse solutions supporting enterprise analytics workloads.Design and develop complex ETL/ELT pipelines using Databricks, Spark, and cloud-native services.Drive MDM strategy, implementation, and integration across business applications and data platforms.Define data integration patterns using APIs, middleware, event-driven architectures, and messaging frameworks.Collaborate with business stakeholders to understand data requirements and translate them into technical solutions.Establish data governance, metadata management, and data quality frameworks.Optimize data processing performance, scalability, and operational monitoring.Define CI/CD processes and deployment standards for data engineering assets.Mentor engineering teams and provide technical leadership throughout the project lifecycle.Support architecture reviews, solution design discussions, and technical decision-making.Ensure compliance with organizational standards, security requirements, and best practices.Soft Skills & Other SkillsCommunication SkillsAbility to communicate complex technical concepts to business and executive stakeholders.Effective verbal, written, and presentation skills.Facilitate architecture reviews, workshops, and stakeholder discussions.Stakeholder ManagementBuild strong relationships with business, IT, and external partners.Manage competing priorities and drive consensus among stakeholders.Demonstrate customer-centric and consultative engagement skills.Leadership SkillsLead cross-functional and geographically distributed teams.Mentor and guide engineers and junior architects.Influence technical decisions through collaboration.Problem Solving & Analytical ThinkingIdentify root causes of complex data and integration challenges.Evaluate multiple solution options and recommend optimal approaches.Strong troubleshooting and performance optimization capabilities.What Success Looks Like (6-12 Months)Successfully deliver enterprise-scale Databricks capabilities.Establish a governed and scalable Lakehouse architecture for analytics and reporting.Improve master data consistency and data quality across key business domains.Implement standardized integration frameworks and reusable patterns.Enable reliable and efficient data movement across multiple enterprise systems.Achieve stakeholder confidence through consistent delivery and technical leadership.Establish engineering best practices, automation, and governance processes.Become a trusted advisor for data platform and integration strategy.Why Join UsClient's platform: Microsoft Partner of the Year (2025), Great Place to Work certified, 19+ years of enterprise delivery excellence.Lead large-scale cloud and data transformation engagements for Fortune 500 customers.Opportunity to architect modern Databricks Lakehouse solutions from the ground up.Work on cutting-edge Data & Analytics, MDM, and AI-enabled platforms.Collaborate with highly skilled cloud, data, and architecture teams.Exposure to enterprise-scale AWS and multi-cloud transformation programs.Accelerate your growth into Solution Architect, Principal Architect, or Data Practice leadership roles.Be part of Client's innovation-driven culture focused on modern data and AI solutions. #J-18808-Ljbffr