Azure Data Architect - freelance

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Requirements

• At least 6 years of professional experience in the Data & Analytics area
• Proven experience as a Data Architect or in a similar role, ideally in a complex organizational setting.
• Strong understanding of data management principles, data modeling techniques, database design and data integration flows.
• Experience in developing and implementing data governance policies, procedures, and frameworks to ensure data integrity and compliance.
• Familiarity with industry best practices and emerging trends in data management and governance.
• Ability to design and develop conceptual, logical, and physical data models that meet business requirements and align with the overall data strategy.
• Strong understanding of data modeling best-practices, e.g. data normalization, denormalization, generalization, and performance optimization techniques.
• Expertise in working with various database technologies, such as relational databases (e.g., Oracle, SQL Server, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB).
• Knowledge of database management systems, data warehousing, data integration technologies, and Big Data solutions.
• Familiarity with cloud-based database, warehouse, and lakehouse platforms.
• Experience in designing and implementing data integration solutions, including Extract,
• Transform, Load (ETL) processes and data pipelines, understanding of data integration patterns and best practices.
• Understanding of Business Intelligence and data analytics requirements, optimization of data storage and processing for reporting needs.
• Excellent communication and presentation skills to effectively articulate complex technical concepts to both technical and non-technical stakeholders.
• Ability to collaborate with cross-functional teams, including business analysts, developers, and data scientists, to understand requirements and drive data-related initiatives.
• Strong analytical and problem-solving abilities to identify data-related issues, propose solutions, and make data-driven decisions.
• Familiarity with data profiling, data cleansing, data harmonization, and data quality assessment techniques.
• Knowledge of data security and privacy regulations, such as GDPR or CCPA, understanding of data encryption, access controls, and data masking techniques to ensure the security of sensitive data.
• Professional certification in data management or related field would be advantageous.

Must have skills

• Data Modelling and Design
• Data Management
• Requirement Gathering and Analysis
• Data Processing
• Technical Leadership
• Data Quality
• Azure Services – Synapse, ADF, ADL
• Technical Implementation and Monitoring
• One of: Python / Pyspark / R / Scala

• CI/CD Automation
• GenAI for Data Engineering

Missing one or two of these qualifications? We still want to hear from you! If you bring a positive mindset, we'll provide an environment where you feel valued and empowered to learn and grow.

• Provides a standard common business vocabulary, expresses strategic data requirements, outlines high level integrated designs to meet these requirements.
• Define and implement data governance policies, procedures, and frameworks to ensure data integrity and compliance.
• Collaborate with stakeholders to align data strategy with business goals and objectives, document current and target state in the form of business process and data journey diagrams.
• Design and develop conceptual, logical, and physical data models that meet business requirements and align with the overall data strategy.
• Define data standards, naming conventions, and data classification guidelines. Ensure data models are scalable, efficient, and optimized for performance.
• Evaluate and select appropriate database technologies and solutions based on organizational needs and requirements.
• Design and oversee the implementation of data platforms, including relational databases, NoSQL databases, data warehousing, and Big Data solutions.
• Optimize database performance, ensure data security, and implement backup and recovery strategies.
• Design data integration solutions, including Extract, Transform, Load (ETL) processes and data pipelines, document source to target mappings.
• Collaborate with IT team and data experts to identify opportunities for data acquisition.
• Understand and follow data architecture patterns for various types of data systems, e.g. data lake platforms, master data management systems, ML enriched data flows.
• Implement data profiling and data cleansing processes to identify and resolve data quality issues.
• Establish data quality standards and implement processes to measure, monitor, and improve data quality.
• Facilitate discussions and workshops to gather requirements and align data initiatives with business goals, prepare data inventory documentation.
• Communicate complex technical concepts effectively to both technical and non-technical stakeholders.
• Stay abreast of industry trends and emerging technologies in data management, analytics, and security.
• Evaluate and recommend new tools, technologies, and frameworks to enhance data architecture capabilities.
• Provide guidance and support to developers and other team members on data-related topics.
• Conduct knowledge sharing sessions and training programs to promote understanding and adoption of data architecture best practices.