Applications Architect (6145-1)

Tri-Force Consulting Services, Inc.•New York, NY

3d•Hybrid

About The Position

The Applications Architect is responsible for designing, developing, implementing, administering, and continuously improving enterprise data and analytics solutions across cloud platforms. The role provides technical leadership in the architecture and delivery of business intelligence, data engineering, data analytics, and artificial intelligence solutions. The 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. The position covers solution architecture and design; Power BI dashboards, reports, data models, and semantic layers; Azure Data Factory pipelines and cloud data integration; administration of Azure, AWS, GCP, and Databricks environments; and evaluation and integration of AI and emerging technologies. It also provides technical leadership through mentoring, design and code reviews, and collaboration on enterprise technology initiatives.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent experience.
10 or more years of experience designing, developing, and supporting enterprise applications, analytics, and data solutions.
Extensive Microsoft Power BI experience, 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 GCP.
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.

Nice To Haves

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.

Responsibilities

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 emerging technologies and platforms; create technical designs, diagrams, and implementation roadmaps.
Design, develop, test, deploy, and maintain enterprise Power BI dashboards, reports, data models, and semantic layers.
Optimize dashboard performance, usability, security, and governance, and translate business reporting and analytical requirements into scalable solutions.
Design, develop, and maintain Azure Data Factory pipelines and other cloud-based data integration solutions.
Build and optimize data ingestion, transformation, and orchestration processes for enterprise data warehouses and data lakes.
Ensure data quality, reliability, scalability, and operational efficiency across data platforms; implement production monitoring, alerting, and automated recovery mechanisms.
Deploy, configure, and manage cloud infrastructure and services across Microsoft Azure, AWS, and GCP.
Design secure, highly available, and cost-effective cloud solutions and implement infrastructure-as-code, automation, and DevOps practices where appropriate.
Monitor cloud platform performance, resource utilization, security compliance, and operational health.
Administer Databricks workspaces, clusters, security, access controls, and performance; support data engineering, machine learning, and analytics workloads.
Troubleshoot Databricks environment issues and work with the vendor as necessary.
Research, evaluate, and recommend technologies and practices for data engineering, analytics, machine learning, Generative AI, and AI solutions.
Assist in developing strategies to integrate AI capabilities into enterprise applications and data platforms; participate in proof-of-concepts and technology assessments.
Provide technical guidance on AI governance, scalability, security, and responsible AI implementation.
Mentor developers, engineers, and analysts on design principles and best practices; review solution designs and code for compliance with standards.
Collaborate with cross-functional teams and serve as a technical subject matter expert for cloud, analytics, and data platform technologies.