Azure Data Solution Architect

About Fusemachines

Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, United States, Canada, and Dominican Republic and more than 400 full-time employees). Fusemachines seeks to bring its global expertise in AI to transform companies around the world.

About the role:

This is a remote contract position, responsible for translation of functional and non-functional requirements, in data and analytics including data integration (ETL/ELT), storage (database design), processing, data modeling and analytics (BI, visualization and Advanced Analytics), into a solution design (low level design), describing it through standardized design artifacts, ensuring alignment to the target architectures, principles, patterns and standards as an input for the rest of the team. 

You will work closely with cross-functional teams to design, implement, and maintain data pipelines, databases, and data models to support the business objectives. Additionally, you will serve as a Azure Cloud solutions subject matter expert (SME) on business logics and collaborate with the Solutioning team on solution design.

We are looking for a skilled Azure Data Solution Architect with a strong background in Agile, Python, SQL, Pyspark, and Azure cloud-based large scale data applications (including Azure Synapse Analytics, Azure Data Lake, Azure Data Factory, Azure SQL Database, and Cosmos DB) with a passion for data quality, performance and cost optimization. The ideal candidate will possess strong technical, analytical, and interpersonal skills and will work in an Agile environment delivering the architecture and design of Data products in the Media Industry (advertising, marketing and public relationship). This role involves hands-on coding and collaboration with multi-disciplined teams to achieve project objectives  agreed with stakeholders, using a variety of technologies.

Qualification & Experience

• Must have a full-time Bachelor's degree in Computer Science or similar from an accredited university.
• Minimum of 5 years of industry experience with large-scale data and analytics solutions.
• 5+ years proven experience in data architecture, ETL development, and database management.
• 3+ years of experience working with Azure cloud services with strong proficiency in SQL, database design, and optimization techniques.
• Strong Experience collaborating closely with product owners, Onsite teams, and the Solutions lead to translate business needs into data solutions.
• Proven experience in designing and implementing large-scale data solutions in Azure. Including:
  • Experience with ETL/ELT tools and frameworks using Azure data factory.
  • Strong experience in data modeling, ETL pipelines, and data integration using Azure data lake house.
• 5+ years of experience with DevOps tools and technologies: GitHub or Azure DevOps: including CI/CD.
• Proven experience in data modeling, management, warehousing, processing/transformation, integration, cleansing and validation.
• Proven experience in Azure Data & Analytics PaaS Services: Azure Data Factory, Azure Data Lake, Azure Synapse Analytics, Azure Databricks.
• Preferred Certifications: 
  • Microsoft Certified: Azure Fundamentals
  • Microsoft Certified: Azure Data Engineer Associate
  • Microsoft Certified: Azure Solutions Architect Expert
  • Nice to have:
    • CDMP certification
    • ITIL
    • TOGAF
    • SAFe
    • Microsoft Certified: Azure AI Engineer Associate

Required skills/ Competencies

• Experience in business processing mapping of data and analytics solutions.
• Strong programming Skills in one or more languages such as Python (must have hands-on experience).
• Strong understanding and experience with SQL and writing advanced SQL queries, including optimization techniques.
• Deep understanding of data architecture concepts, principles, techniques, and best practices, including data modeling, data management, data migration, data integration, data warehousing, business intelligence, visualization and advanced analytics (ML/AI). Being able to design and architect effective data and analytics solutions that align with business objectives and priorities:
  • Proficiency in designing highly available, scalable, and resilient data solutions that can handle varying workloads and demand spikes.
  • Knowledge of disaster recovery strategies and backup and restore mechanisms in Azure.
• Strong experience in designing and implementing Data Warehousing, data lake and data lake house, solutions in Azure.
• Strong experience in designing and implementing scalable and distributed Data Processing Technologies using Spark/PySpark (must have hands-on experience), DBT and Kafka, to be able to handle large volumes of data.
• Strong experience in designing and implementing data pipelines and efficient ELT/ETL processes, batch and real-time, in Azure (including Azure Data Factory, Azure Synapse Analytics, Azure Data Lake) and using open source solutions being able to develop custom integration solutions as needed, including Data Integration from different sources such as APIs, databases, flat files, Apache Parquet, event streaming, including cleansing, transformation and validation of the data.
• Deep knowledge in cloud computing specifically in Microsoft Azure services related to data and analytics, such as Azure Data Factory, Azure Synapse Analytics, Azure Data Lake, Azure Functions, Azure Stream Analytics, Azure Blob Storage, Azure Data Lake Storage, Azure SQL Database, PowerBI, etc.
• Experience in Orchestration using technologies like Databricks workflows and Apache Airflow.
• Deep knowledge of data analytics architecture and services, including BI (PowerBI or Tableau).
• Must be familiar with advanced analytics, AI/ML services and tools, and the ability to integrate advanced analytics, machine learning, and AI capabilities into data solutions.
• Deep knowledge of data governance architecture, design and implementation, including Data Quality, Data Cataloging, Metadata Management and Data Lineage.
• Ability to design solutions that ensure data privacy, confidentiality, and regulatory compliance including GDPR, HIPAA.
• Strong understanding of the software development lifecycle (SDLC), including Agile methodologies.
• Strong understanding of DevOps principles, including continuous integration, continuous delivery (CI/CD), infrastructure as code (IaC), configuration management, automated testing and cost management.
• Strong knowledge and hands-on experience of DevOps tools and technologies (GitHub and Azure DevOps), including project management software (Jira, Azure Boards or similar), source code management (GitHub, Azure Repos, Bitbucket or similar), CI/CD system (GitHub actions, Azure Pipelines, Jenkins or similar) and binary repository manager (Azure Artifacts or similar).
• Experience using tools like Azure Resource Manager templates, Terraform, or Ansible to define and manage infrastructure is a plus.
• Ability to design and architect monitoring and alerting using Azure Monitor, Application Insights, or other monitoring tools like Datadog, CloudWatch, Prometheus.
• Knowledge of Azure security practices, including network security groups, identity and access management with Azure Active Directory, encryption, and compliance standards.
• Ability to design and architect security controls and best practices within data and analytics solutions, including proficient knowledge and working experience on various cloud security vulnerabilities and ways to mitigate them. Should be able to research thoroughly and design and architect industry standard tools to minimize & mitigate security loopholes as and when required.
• Good grasp on UML Diagrams such as Use Case Diagrams and Flow Diagrams.
• Strategic thinker who can develop and implement data strategies that align with the organization's overall business strategy, identifying opportunities for data-driven innovation and growth and develop strategies to take advantage of those opportunities.
• Effective leadership and Management: can manage a team of data engineers, data quality engineers, data analyst and other data-related roles, providing guidance, mentorship, and coaching to the team and ensure that the team is meeting its goals and objectives.
• Effective and strong written and verbal communication skills to collaborate with cross-functional teams, including DevOps engineers, data engineers, data analysts, data scientists, developers, and operations teams, and ability to think strategically and work cross-functionally with multiple stakeholders and audiences.
• Effective communicator who can collaborate with different departments and stakeholders to promote and implement data architecture and strategy frameworks, being able to communicate complex data architecture and strategy concepts in a way that is understandable to a wide range of audiences, with the ability to translate complex data architectures to non-technical stakeholders.
• Skilled in analyzing data and identifying patterns and trends that can inform data architecture and strategy decisions, and be able to identify and solve problems related to code, design and proposing optimization solutions.
• Good understanding of the organization's business objectives, priorities, and operations to be able to align data architecture and strategy frameworks with the organization's overall business goals.
• Experience in project management and managing data architecture and strategy projects from conception to completion. Should be able to identify and mitigate project risks and ensure that projects are completed on time and within budget.
• Ability to document processes, procedures, and deployment configurations.
• Strong analytical skills to identify and address technical issues, performance bottlenecks, latency issues, data processing inefficiencies and system failures.
• Proficiency in debugging and troubleshooting issues in complex data and analytics environments.
• Have presented architecture deliverables to governance forums such as Arch. Review Boards and Design Authorities.
• A willingness to stay updated with the latest Data and Analytics services trends, and best practices in the field.
•  Self-motivated and ability to work well in a team.

Responsibilities

• Meet with stakeholders to understand the big picture and requirements. Driving the detailed design and architectural discussions as well as customer requirements sessions to support the implementation of code and procedures for big data products.
• Requirement Analysis and Solution Design: Translation of functional and non-functional requirements in data and analytics, into a solution design (low level design), describing it through standardized design artifacts, ensuring alignment to the target architectures, principles, patterns and standards as an input for the DevOps/DataOps Engineer to build the infrastructure as code.
• Design and implement data architecture frameworks, patterns, best practices and models that align with the organization's business goals, objectives and priorities, working closely with stakeholders across the products/organization.
• Establish and implement data architecture standards to ensure consistency, accuracy, and reliability of data across the organization, working closely with data governance and data management teams to ensure that data architecture standards are aligned with other data-related policies and procedures.
• Oversee data architecture projects and ensure that they are completed on time, within budget, and meet business requirements. Working closely with product teams and stakeholders to identify and resolve issues and ensure that data architecture projects are successful.
• Lead data strategy development: develop and implement data strategies that align with the organization's overall business strategy. 
• Provide guidance and support to data operations, data engineers, data analyst, data scientist and other data-related roles across the organization as a subject matter expert in data architecture and strategy.
• Partner with Technology and Business leadership to define strategies, make strategic recommendations and align technology strategy to business strategy.
• Lead data architecture initiatives: including developing and implementing data architecture roadmaps, defining data architecture priorities, aligned with business objectives, delivering solution architecture in data and analytics including:
  • Architect end-to-end data solutions on Azure platform, considering data integration, data storage, data processing/transformation/cleansing/validation, analytics and BI, reporting and visualization, and advanced analytics (AI/ML) requirements,  for transformation and modernization of enterprise data solutions using Azure cloud data technologies.
  • Analyze current business practices, processes, and procedures as well as identify relevant Microsoft Azure Data & Analytics IaaS, SaaS and PaaS services.
  • Design secure, scalable, reliable, efficient and performant architectures that leverage appropriate Azure services and adhere to standards and best practices.
  • Define data models and storage strategies that optimize data retrieval, storage costs, and performance within Azure data services.
  • Design data governance solutions, methods and policies including metadata management, cataloging, quality assurance, retention/archival/decommission and lineage management.
  • Design identity and access management.
• Monitor and optimize the performance of the data architecture, ensuring cost-effective use of Azure resources.
• Define and Implement Disaster recovery strategies for Azure cloud data environments.
• Manage and optimize database systems, including building and updating stored procedures and functions.
• Code reviews to ensure code quality, performance, and adherence to coding standards.
• Monitor and troubleshoot data pipelines, database performance issues, and data quality problems.
• Create and maintain architectural diagrams, solution blueprints, and documentation that clearly explain the design and implementation details for data and analytics solutions.
• Design and develop PoCs to validate the feasibility of new data and analytics technologies, tools, or approaches within the Azure ecosystem.
• Communicate complex technical concepts to both technical and non-technical stakeholders.
• Commit to working closely with development teams and other stakeholders to discover the best technological solutions and products, develop them together, and implement them properly. Being actively involved in the development and testing activities for big data applications.
• Work independently and collaboratively on a multi-disciplined project team in an Agile development environment, actively participating in Agile ceremonies to clarify, analyze, assess requirements to meet product deliverables.
• Stay updated with the latest trends in Data and Analytics, emerging technologies and best practices, specially within Azure services to continuously improve our data infrastructure and processes.

Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.