Application Architect – Data & Analytics (Power BI, Azure Data Factory & Databricks)

SoHo Dragon; New York (NY); On-site; USD 85,000 - 121,000; Full time

Job summary

SoHo Dragon in New York City seeks an Application Architect – Data & Analytics with deep expertise in Power BI, Azure Data Factory, and Databricks to design enterprise data solutions.

You will lead BI and data engineering initiatives, develop scalable architectures, and guide cloud deployments across Azure, AWS, and GCP. This 12-month, on-site engagement requires strong communication and hands-on leadership.

Qualifications

• 10+ years of experience in enterprise data, analytics, or solution architecture.
• Strong hands-on Power BI experience including dashboards, DAX, and semantic models.
• Strong experience with Azure Data Factory pipelines and data integration.
• Hands-on experience administering and supporting Databricks.
• Experience managing cloud resources across Azure, AWS, and GCP.
• 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.
• Excellent communication and problem-solving skills.
• Bachelor's degree in a related field or equivalent experience.

Responsibilities

• 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.
• Develop and maintain Power BI dashboards, reports, and data models.
• Optimize performance, security, usability, and governance of BI solutions.
• Translate business reporting requirements into scalable BI solutions.
• Develop and maintain Azure Data Factory pipelines.
• Build data ingestion, transformation, and orchestration processes.
• Support data warehouses and data lakes and ensure data quality.
• Deploy and manage Databricks workspaces, clusters, and access controls.
• Support cloud deployments across Azure, AWS, and GCP.
• Design secure, highly available cloud solutions and enable DevOps practices.
• Evaluate AI technologies and integrate AI into data platforms.
• Provide technical leadership and review designs and code.

Skills

Analytical thinking

Communication

Problem solving

Leadership

Cloud experience

Education

Bachelor's degree or equivalent

Tools

Power BI

Azure Data Factory

Databricks

SQL

Azure/AWS/GCP

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.

Core Skills

• Power BI
• Azure Data Factory
• Databricks
• Azure / AWS / GCP
• SQL
• Data Engineering
• Data Warehousing / Data Lakes
• Solution Architecture
• DevOps / CI/CD
• AI / Machine Learning