10+ years in enterprise applications, data, analytics, or solution architecture.
Hands-on experience with Power BI, including dashboards and DAX.
Strong expertise in Azure Data Factory for ETL/ELT processes.
Experience administering Databricks environments.
Proficient in managing cloud resources across Azure, AWS, and GCP.
Solid understanding of data warehouses, data lakes, and analytics architecture.
Strong SQL skills with a focus on data integration and performance optimization.
Knowledge of DevOps practices and cloud security.
Responsibilities
Design scalable enterprise data and analytics architectures.
Define technical standards for data, reporting, and AI.
Create solution designs and implementation roadmaps.
Develop and maintain Power BI dashboards and reports.
Build and maintain Azure Data Factory pipelines.
Administer Databricks workspaces and security controls.
Deploy and manage services across Azure, AWS, and GCP.
Evaluate and integrate AI technologies into enterprise applications.
Benefits
Opportunity to work onsite in NYC, fostering collaboration.
Engagement in cutting-edge data and AI technologies.
Exposure to large enterprise and public-sector projects.
Potential for professional growth in cloud and analytics domains.
Full Job Description
Job Title: Application Architect - Data & Analytics (Power BI, Azure Data Factory & Databricks)
Duration: 12 months(37.5 hrs per week)
Location: 2 Broadway, NYC - 100% Onsite
Pay rate: $75/hr on C2C
Position Summary
The Application Architect will design and support enterprise data, analytics, and cloud solutions, with a focus on Power BI, Azure Data Factory, Databricks, and cloud platforms. The role provides technical leadership across business intelligence, data engineering, analytics, and AI initiatives.
Required Qualifications
10+ years of experience in enterprise applications, data, analytics, or solution architecture.
Strong hands-on Power BI experience, including dashboards, DAX, semantic models, and workspace administration.
Strong experience with Azure Data Factory, including ETL/ELT pipelines and data integration.
Hands-on experience administering and supporting Databricks.
Experience managing cloud resources in Azure, AWS, and GCP.
Strong knowledge of data warehouses, data lakes, dimensional modeling, and analytics architecture.
Strong SQL, data integration, and performance optimization experience.
Knowledge of DevOps, CI/CD, infrastructure automation, and cloud security.
Strong analytical, communication, and problem-solving skills.
Bachelor's degree in a related field or equivalent experience.
Preferred Qualifications
Azure, AWS, and/or GCP certifications.
Databricks certification or equivalent experience.
Experience with Machine Learning, Generative AI, and AI platforms.
Knowledge of data governance, metadata management, and data quality.
Large enterprise or public-sector experience.
Key Responsibilities
Architecture & Design
Design scalable enterprise data and analytics architectures.
Define technical standards and best practices for data, reporting, analytics, and AI.
Create solution designs, architecture diagrams, and implementation roadmaps.
Evaluate new technologies and platforms.
Power BI
Develop and maintain Power BI dashboards, reports, semantic models, and data models.
Optimize performance, security, usability, and governance.
Translate business reporting requirements into scalable BI solutions.
Azure Data Factory / Data Engineering
Develop and maintain Azure Data Factory pipelines.
Build data ingestion, transformation, and orchestration processes.
Support enterprise data warehouses and data lakes.
Ensure data quality, scalability, reliability, monitoring, and recovery.
Databricks
Administer Databricks workspaces, clusters, security, and access controls.
Support data engineering, analytics, and machine learning workloads.
Perform troubleshooting and performance tuning.
Cloud
Deploy and manage services across Azure, AWS, and GCP.
Design secure, highly available, and cost-effective cloud solutions.
Support infrastructure automation and DevOps practices.
Monitor cloud performance, security, and resource utilization.
AI & Analytics
Evaluate Machine Learning, Generative AI, and AI technologies.
Support AI integration into enterprise applications and data platforms.
Participate in POCs and technology assessments.
Provide guidance on AI governance, security, and scalability.
Technical Leadership
Provide technical guidance to developers, engineers, and analysts.
Review solution designs and code.
Support enterprise technology initiatives.
Serve as an SME for cloud, data, analytics, and BI technologies.
