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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Databricks Platform Architect - **Company:** Argyle Associates Ltd - **Location:** Jersey City, NJ, United States - **Experience:** Expert - **Contract:** Temporary to permanent - **Skills:** Airflow, Amazon Web Services, Amazon S3, Application Frameworks, Microsoft Azure, Continuous Integration, Data Architecture, Information Engineering, Data Governance, DevOps, Github, Python (Programming Language), Performance Tuning, SQL Databases, Data Streaming, Workflow Management Systems, Cloud Platform System, Apache Spark, Event Driven Architecture, Data Lakes, Pyspark, Apache Kafka, Data Management, Machine Learning Operations, Cloud Integration, Terraform, Data Pipelines, Serverless Computing, Jenkins, Databricks - **Published:** August 20, 2026 - **Apply:** https://www.careerjet.com/jobad/us85bf02582036f3c352ca8aae8335a839 ## About the Role * Advanced proficiency in SQL and Python * Hands-on experience with Delta Lake, Medallion Architecture, and Unity Catalog * Strong experience with at least one cloud platform (AWS / Azure / GCP) * Experience with CI/CD tools (Azure DevOps, Jenkins, GitHub Actions) * Knowledge of workflow orchestration tools (Airflow or equivalent) Good to Have * Databricks certifications (Associate / Professional) * Experience with Databricks SQL & dashboards * Exposure to ML pipelines (MLflow) * Experience with Kafka or event-driven architectures * Domain experience in Finance / Retail / Healthcare What Makes You a Great Fit * Strong architectural mindset with ability to design scalable data platforms * Deep understanding of performance tuning and cost optimization * Ability to balance technical depth with business impact * Excellent communication and stakeholder management skills ## Description We are seeking a highly skilled Databricks Architect to lead the design and implementation of next-generation data platforms built on the Lakehouse paradigm. This role goes beyond pipeline development-you will own the Databricks platform architecture end-to-end, driving scalability, governance, performance, and cost optimization across enterprise data ecosystems. Databricks Platform Architecture * Architect and implement enterprise-scale Databricks environments (dev/test/prod) * Define workspace strategy, cluster policies, and job orchestration frameworks * Design secure, scalable Lakehouse architecture using Delta Lake Data Engineering & Processing * Build and optimize high-performance data pipelines using Apache Spark (PySpark / Scala) * Implement Medallion Architecture (Bronze, Silver, Gold) * Develop batch and real-time streaming pipelines using Structured Streaming Governance, Security & Compliance * Implement fine-grained access control using Unity Catalog * Define enterprise-wide data governance, lineage, and auditing frameworks * Ensure compliance with security and regulatory standards Performance & Cost Optimization * Optimize workloads using partitioning, caching, and Photon engine * Design cost-efficient cluster strategies (autoscaling, spot instances, DBU optimization) * Monitor and improve query and pipeline performance at scale DevOps & Automation * Implement CI/CD pipelines for Databricks using Azure DevOps, Jenkins, or GitHub Actions * Enable Infrastructure as Code using Terraform or equivalent * Standardize reusable frameworks and engineering best practices Cloud Integration * Architect Databricks solutions on AWS / Azure / GCP * Integrate with cloud-native services (AWS S3/Glue, Azure ADLS/ADF, etc.) ## Related Videos - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Why Event-Driven Architecture Isn’t About Speed (and When You Actually Need It)](https://www.wearedevelopers.com/magazine/745-why-event-driven-architecture-isn-t-about-speed-and-when-you-actually-need-it) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)