Azure Data Engineering Architect - freelance

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Tasks

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Collaborate with stakeholders to understand business requirements and translate them into data engineering solutions.

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Design and oversee the overall data architecture and infrastructure, ensuring scalability, performance, security, maintainability, and adherence to industry best practices.

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Define data models and data schemas to meet business needs, considering factors such as data volume, velocity, variety, and veracity.

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Select and integrate appropriate data technologies and tools, such as databases, data lakes, data warehouses, and big data frameworks, to support data processing and analysis.

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Create scalable and efficient data processing frameworks, including ETL (Extract, Transform, Load) processes, data pipelines, and data integration solutions.

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Ensure that data engineering solutions align with the organization's long-term data strategy and goals.

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Evaluate and recommend data governance strategies and practices, including data privacy, security, and compliance measures.

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Collaborate with data scientists, analysts, and other stakeholders to define data requirements and enable effective data analysis and reporting.

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Provide technical guidance and expertise to data engineering teams, promoting best practices and ensuring high-quality deliverables. Support to team throughout the implementation process, answering questions and addressing issues as they arise.

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Oversee the implementation of the solution, ensuring that it is implemented according to the design documents and technical specifications.

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Stay updated with emerging trends and technologies in data engineering, recommending and implementing innovative solutions as appropriate.

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Conduct performance analysis and optimization of data engineering systems, identifying and resolving bottlenecks and inefficiencies.

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Ensure data quality and integrity throughout the data engineering processes, implementing appropriate validation and monitoring mechanisms.

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Collaborate with cross-functional teams to integrate data engineering solutions with other systems and applications.

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Participate in project planning and estimation, providing technical insights and recommendations.

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Document data architecture, infrastructure, and design decisions, ensuring clear and up-to-date documentation for implementation, reference and knowledge sharing.

Requirements

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Proven work experience as a Data Engineering Architect or a similar role and strong experience in in the Data & Analytics area.

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Strong understanding of data engineering concepts, including data modeling, ETL processes, data pipelines, and data governance.

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Expertise in designing and implementing scalable and efficient data processing frameworks.

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In-depth knowledge of various data technologies and tools, such as relational databases, NoSQL databases, data lakes, data warehouses, and big data frameworks (e.g., Hadoop, Spark).

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Experience in selecting and integrating appropriate technologies to meet business requirements and long-term data strategy.

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Ability to work closely with stakeholders to understand business needs and translate them into data engineering solutions.

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Strong analytical and problem-solving skills, with the ability to identify and address complex data engineering challenges.

- Proficiency in Python, PySpark, SQL.

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Familiarity with cloud platforms and services, such as AWS, GCP, or Azure, and experience in designing and implementing data solutions in a cloud environment.

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Knowledge of data governance principles and best practic