Role: Application Architect
Location: 2 Broadway, New York, NY (Hybrid with 2 days remote and 3 days on site)
Duration: Long Term
Job Description:
The Application Architect is responsible for the design, development, implementation, administration, and continuous improvement of enterprise data and analytics solutions across cloud platforms. This role provides technical leadership in the architecture and delivery of business intelligence, data engineering, data analytics, and artificial intelligence solutions. The Application Architect collaborates with business stakeholders, data engineers, analysts, and technology teams to develop scalable, secure, and high-performing data platforms that support enterprise decision-making and innovation.
Key Responsibilities
Solution Architecture & Design
- Design and implement scalable enterprise data and analytics architectures using cloud-native technologies.
- Support technical standards, best practices, and architectural guidelines for data integration, reporting, analytics, and AI solutions.
- Research and evaluate the use of emerging technologies and platforms.
- Create technical designs, diagrams, and implementation roadmaps.
Business Intelligence & Analytics
- Design, develop, test, deploy, and maintain enterprise Power BI dashboards, reports, data models, and semantic layers.
- Optimize dashboard performance, usability, security, and governance.
- Collaborate with business users to translate reporting and analytical requirements into scalable solutions.
- Data Engineering & Integration
- Design, develop, and maintain Azure Data Factory pipelines and other cloud-based data integration solutions.
- Build and optimize data ingestion, transformation, and orchestration processes supporting enterprise data warehouses and data lakes.
- Ensure data quality, reliability, scalability, and operational efficiency across data platforms.
- Implement monitoring, alerting, and automated recovery mechanisms for production workloads.
Cloud Platform Administration
- Deploy, configure, and manage cloud infrastructure and services across Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (Google Cloud Platform).
- Design secure, highly available, and cost-effective cloud solutions.
- Implement infrastructure-as-code, automation, and DevOps practices where appropriate.
- Monitor platform performance, resource utilization, security compliance, and operational health.
Databricks Administration
- Administer and maintain the Databricks platform, including workspace configuration, cluster management, security, access controls, and performance tuning.
- Support data engineering, machine learning, and analytics workloads within Databricks.
- Troubleshoot and resolve technical issues affecting Databricks environments, working with the vendor as necessary.
AI, Data Analytics & Innovation
- Research, evaluate, and recommend innovative technologies and best-practice approaches for Data Engineering, Data Analytics, Machine Learning, Generative AI, and Artificial Intelligence solutions.
- Assist in the development of strategies for integrating AI capabilities into enterprise applications and data platforms.
- Participate in proof-of-concepts and technology assessments to support strategic initiatives.
- Provide technical guidance on AI governance, scalability, security, and responsible AI implementation.
Technical Leadership
- Mentor developers, engineers, and analysts on design principles and best practices.
- Review solution designs and code to ensure compliance with standards.
- Collaborate with cross-functional teams to deliver enterprise technology initiatives.
- Serve as a technical subject matter expert for cloud, analytics, and data platform technologies.
Required Qualifications
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent experience.
- 10+ years of experience designing, developing, and supporting enterprise applications, analytics, and data solutions.
- Extensive experience with Microsoft Power BI, including dashboard development, DAX, semantic models, and workspace administration.
- Strong experience designing and maintaining Azure Data Factory pipelines and cloud-based ELT/ETL solutions.
- Experience administering and supporting Databricks environments.
- Experience deploying and managing cloud resources in Azure, AWS, and Google Cloud Platform.
- Strong understanding of data warehousing, data lakes, dimensional modeling, and enterprise analytics architectures.
- Experience with SQL, data integration, and performance optimization.
- Knowledge of DevOps, CI/CD, infrastructure automation, and cloud security best practices.
- Excellent analytical, communication, and problem-solving skills.
Preferred Qualifications
- Cloud certifications in Azure, AWS, and/or Google Cloud.
- Databricks certification or equivalent experience.
- Experience with machine learning, AI platforms, and Generative AI solutions.
- Knowledge of data governance, metadata management, and data quality frameworks.
- Experience working in large enterprise or public-sector environments.
Key Competencies:
- Data Engineering
- Business Intelligence
- Cloud Computing
- Artificial Intelligence
- Solution Design
- Data Analytics
- Platform Administration
