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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # solution Architect - **Company:** Infinitive - **Location:** United States - **Experience:** Experienced - **Salary:** $140,000 - $210,000 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Microsoft Azure, Cloud Computing, Software Quality, Computer Programming, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Masking, Data Vault Modeling, Dimensional Modeling, Github, Apache Hadoop, Data Intelligence, Python (Programming Language), Machine Learning, Performance Tuning, Power BI, DataOps, Cloudera, Azure Data Lake, Search Technologies, Software Engineering, SQL Databases, Data Streaming, Systems Integration, Tableau (Software), Teradata SQL, Feature Store, Google Cloud, Cloud Platform System, Netezza, Retrieval-Augmented Generation, Snowflake, Apache Spark, Multi-Cloud, Amazon Virtual Private Cloud (VPC), Gitlab, SC Clearance, Data Lakes, Pyspark, Core Data, Optimization Algorithms, Machine Learning Operations, Terraform, Data Pipelines, Serverless Computing, Databricks - **Published:** November 11, 2026 - **Apply:** http://infinitive.theresumator.com/apply/jobs/details/DALb3SXdZD ## About the Role Required Experience & Technical Skills * Architectural Experience: 8+ years in data architecture, data engineering, or enterprise software development, with at least 3+ years architecting enterprise solutions centered on Apache Spark and the Databricks Data Intelligence Platform. * Certifications: + Databricks: Databricks Certified Data Engineer Professional or Databricks Certified Machine Learning Professional. * Cloud Platform Mastery: Deep architectural proficiency in at least one major cloud platform (AWS, Azure, or GCP), including VPC/VNet networking, private endpoints, cloud IAM/Entra ID integration, and cloud object storage (S3/ADLS Gen2/GCS). * Data Modeling & Governance: Mastery of modern data modeling methodologies (dimensional modeling, Data Vault, Medallion design) and hands-on production experience implementing Unity Catalog across multi-workspace environments. * Coding & Automation: Advanced programming skills in Python, PySpark, and SQL, alongside production experience with Infrastructure as Code (Terraform) and orchestrators (Databricks Workflows, Airflow). * Delivery Leadership: Proven background leading technical delivery teams, breaking down complex functional requirements into architectural blueprints and user stories, and resolving critical delivery blockers. Preferred Qualifications & Certification * Modern Data Stack Integrations: Hands-on experience integrating Databricks with BI tools (Power BI, Tableau), reverse ETL, dbt, or data observability platforms. * Security & Compliance: Experience delivering architectures compliant with enterprise regulatory frameworks (HIPAA, HITRUST, SOC2, FedRAMP). * Clearance: Active Public Trust or Secret clearance (or eligibility to obtain) for regulated/public sector client engagements is a plus. ## Description The Solution Architect, Delivery is a premier technical leadership role responsible for the architecture, design, and end-to-end technical delivery of complex Lakehouse and Data Intelligence Platform solutions. Operating at the apex of solution design and hands-on execution, the DSA bridges client executive vision with production-grade engineering reality. In this role, you will lead the technical vision across multi-cloud environments (AWS, Azure, GCP), architect scalable data pipelines and governance frameworks, and guide engineering pods through intricate technical migrations. The solution Architect works closely with client enterprise architects, Databricks partner engineering, and Infinitive delivery teams to ensure every implementation adheres to modern performance, security, cost-efficiency, and architectural governance standards., Technical Architecture & Solution Design * Lakehouse Architectural Ownership: Design enterprise-scale, production-ready Lakehouse solutions leveraging the Databricks Data Intelligence Platform, Medallion Architecture (Bronze/Silver/Gold), Delta Lake, and Databricks SQL. * Unified Governance & Security: Architect and configure enterprise security and governance models using Unity Catalog, row/column-level filtering, data masking, attribute-based access controls (ABAC), and Delta Sharing. * Legacy Modernization & Migration: Lead architectural strategy and technical execution for migrating legacy enterprise data warehouses and Hadoop platforms (e.g., Teradata, Netezza, Snowflake, Cloudera) to Databricks. * Modern Ingestion & Processing: Define patterns for both batch and low-latency streaming workloads utilizing Structured Streaming, Delta Live Tables (DLT), Auto Loader, and Apache Spark optimization techniques. Hands-On Technical Leadership & Governance * Technical Oversight & Code Quality: Lead engineering pods by example-establishing reference architectures, conducting architectural reviews, reviewing pull requests, and standardizing CI/CD pipelines (GitHub Actions, GitLab, Azure DevOps) using Terraform and Databricks Asset Bundles (DABs). * Performance Tuning & Optimization: Diagnose and resolve complex Spark and Delta performance bottlenecks, optimizing query execution plans, partitioning strategies, Z-Ordering, caching, and Photon engine configurations. * FinOps & Cost Observability: Establish compute governance best practices, designing cluster policies, auto-termination/autoscaling rules, serverless compute configurations, and chargeback/showback tagging models to optimize DBU consumption. * AI & Advanced Analytics Enablement: Partner with Machine Learning and AI engineers to integrate MLflow, Feature Store, Databricks Model Serving, and Vector Search/RAG pipelines into core data platforms. Client Advisory & Partner Engagement * Technical Advisory & Strategy: Act as the primary technical authority and trusted advisor to client Chief Architects, Directors of Engineering, and CDOs, leading technical workshops, architectural design sessions (ADS), and proof-of-concept (POC) evaluations. * Databricks Ecosystem Alignment: Collaborate directly with Databricks Partner Solutions Architects (PSAs) and field engineering to evaluate preview features, adopt cutting-edge platform capabilities, and ensure best-practice alignment. * Practice IP & Thought Leadership: Harvest repeatable architectural blueprints, reference architectures, migration accelerators, and boilerplate configurations to enrich Infinitive's intellectual property library.