Azure Data Architect/Modeller
Azure Data Architect/Modeler
Remote work
Duration: 12 Months+
Primary Duties and Accountabilities
• Design and implement scalable data architectures, including conceptual, logical, and physical models, to meet business objectives and support data-driven decision-making across the organization.
• Lead the development and optimization of data pipelines and data warehousing solutions, ensuring data accuracy, consistency, and accessibility for reporting and business intelligence.
• Collaborate with business and IT teams to translate business needs into comprehensive data solutions, aligning them with strategic goals while maintaining high data quality, integrity, and security.
• Establish and enforce data governance practices to ensure compliance with regulatory standards and industry best practices, while fostering a culture of data stewardship and responsibility.
• Stay informed about emerging data technologies, tools, and trends, recommending and implementing innovative solutions to enhance organizational data capabilities and business insights.
• Mentor and guide cross-functional teams in the design and implementation of data solutions, including data platforms, ensuring they provide actionable and valuable insights for business users.
• Continuously review and optimize existing data systems, identifying opportunities for improvement in efficiency, performance, and user satisfaction, while mitigating potential risks and ensuring project success.
• Communicate data strategies and complex technical concepts effectively to both technical and non-technical stakeholders, ensuring alignment with business needs and fostering strong collaboration across teams.
• Promote a data-driven culture by educating stakeholders on best practices for data management, reporting tools, and leveraging data insights to support strategic business decisions.
• Ensure all data solutions adhere to enterprise architecture frameworks, promoting consistency, scalability, and ongoing development while supporting the growth and development of data teams.
Minimum Qualifications
• Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field.
• 10+ years of experience in IT, with at least 5 years in data architecture, data engineering, or similar role. Proven expertise in designing and delivering large-scale data solutions.
• Hands-on experience with Microsoft Azure services, including Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and other Azure data components.
• Extensive expertise in data architecture, including data modeling, ETL pipelines, data lakes, and business intelligence solutions, with proficiency in Big Data technologies (e.g., Hadoop, Spark, Kafka) and both relational and NoSQL databases (e.g., SQL Server, MongoDB), along with a strong understanding of Data Lake, Data Mart, DataMesh, and Data Hub concepts.
• Proficiency in data modeling for both OLTP and OLAP systems, and familiarity with data formats such as Avro and Parquet.
• Ability to define enterprise-level data standards and contribute to the selection of appropriate tools.
• Solid understanding of data governance, data security best practices, and cybersecurity fundamentals in the context of cloud-based and enterprise data systems.
• Experience in data profiling and data cataloging to ensure high-quality, well-structured data. Ability to maintain up-to-date Data Dictionaries in a disciplined manner.
• Hands-on experience with data modeling tools such as Erwin, Power Designer, or similar platforms for creating and managing complex data models.
• Experience in analyzing functional and non-functional business requirements and translating them into technical data requirements.
• Proven ability to lead cross-functional teams, manage large-scale projects, and collaborate with senior leadership to define and align data strategies with business goals.
• Excellent communication skills to convey complex technical concepts to both technical and business stakeholders. Strong consulting and negotiation skills with internal teams and external vendors.
Azure Data Architect/Modeler
Remote work
Duration: 12 Months+
Primary Duties and Accountabilities
• Design and implement scalable data architectures, including conceptual, logical, and physical models, to meet business objectives and support data-driven decision-making across the organization.
• Lead the development and optimization of data pipelines and data warehousing solutions, ensuring data accuracy, consistency, and accessibility for reporting and business intelligence.
• Collaborate with business and IT teams to translate business needs into comprehensive data solutions, aligning them with strategic goals while maintaining high data quality, integrity, and security.
• Establish and enforce data governance practices to ensure compliance with regulatory standards and industry best practices, while fostering a culture of data stewardship and responsibility.
• Stay informed about emerging data technologies, tools, and trends, recommending and implementing innovative solutions to enhance organizational data capabilities and business insights.
• Mentor and guide cross-functional teams in the design and implementation of data solutions, including data platforms, ensuring they provide actionable and valuable insights for business users.
• Continuously review and optimize existing data systems, identifying opportunities for improvement in efficiency, performance, and user satisfaction, while mitigating potential risks and ensuring project success.
• Communicate data strategies and complex technical concepts effectively to both technical and non-technical stakeholders, ensuring alignment with business needs and fostering strong collaboration across teams.
• Promote a data-driven culture by educating stakeholders on best practices for data management, reporting tools, and leveraging data insights to support strategic business decisions.
• Ensure all data solutions adhere to enterprise architecture frameworks, promoting consistency, scalability, and ongoing development while supporting the growth and development of data teams.
Minimum Qualifications
• Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field.
• 10+ years of experience in IT, with at least 5 years in data architecture, data engineering, or similar role. Proven expertise in designing and delivering large-scale data solutions.
• Hands-on experience with Microsoft Azure services, including Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and other Azure data components.
• Extensive expertise in data architecture, including data modeling, ETL pipelines, data lakes, and business intelligence solutions, with proficiency in Big Data technologies (e.g., Hadoop, Spark, Kafka) and both relational and NoSQL databases (e.g., SQL Server, MongoDB), along with a strong understanding of Data Lake, Data Mart, DataMesh, and Data Hub concepts.
• Proficiency in data modeling for both OLTP and OLAP systems, and familiarity with data formats such as Avro and Parquet.
• Ability to define enterprise-level data standards and contribute to the selection of appropriate tools.
• Solid understanding of data governance, data security best practices, and cybersecurity fundamentals in the context of cloud-based and enterprise data systems.
• Experience in data profiling and data cataloging to ensure high-quality, well-structured data. Ability to maintain up-to-date Data Dictionaries in a disciplined manner.
• Hands-on experience with data modeling tools such as Erwin, Power Designer, or similar platforms for creating and managing complex data models.
• Experience in analyzing functional and non-functional business requirements and translating them into technical data requirements.
• Proven ability to lead cross-functional teams, manage large-scale projects, and collaborate with senior leadership to define and align data strategies with business goals.
• Excellent communication skills to convey complex technical concepts to both technical and business stakeholders. Strong consulting and negotiation skills with internal teams and external vendors.
