Azure Data Engineering Architect - Freelance (Part-time)

Lingaro is an established global technology partner operating since 2008 with over 1,600 professionals across 7 global locations.

• Proven work experience as a Data Engineering Architect or a similar role in the Data & Analytics area.
• Strong understanding of data engineering concepts including data modeling, ETL processes, data pipelines, and data governance.
• Expertise in designing and implementing scalable and efficient data processing frameworks.
• In-depth knowledge of data technologies and tools such as relational databases, NoSQL databases, data lakes, data warehouses, and big data frameworks (e.g., Hadoop, Spark).
• Experience selecting and integrating technologies to meet business requirements and long-term data strategy.
• Ability to translate business needs into data engineering solutions.
• Strong analytical and problem-solving skills.
• Proficiency in Python, PySpark, SQL.
• Familiarity with cloud platforms and services including AWS, GCP, or Azure with experience in designing cloud data solutions.
• Knowledge of data governance principles, data privacy, and security regulations.
• Excellent communication and collaboration skills.
• Experience leading and mentoring data engineering teams.
• Familiarity with agile methodologies.
• Continuous learning mindset to stay updated with data engineering advancements.
• Strong project management skills including prioritization and timeline management.
• Strong understanding of distributed computing principles such as parallel processing, data partitioning, and fault-tolerance.
• Bachelor's degree in Computer Science, Information Technology, or related field; Master's degree preferred.

• Collaborate with stakeholders to understand business requirements and translate them into data engineering solutions.
• Design and oversee the overall data architecture and infrastructure, ensuring scalability, performance, security, maintainability, and adherence to industry best practices.
• Define data models and data schemas to meet business needs, considering factors such as data volume, velocity, variety, and veracity.
• 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.
• Create scalable and efficient data processing frameworks, including ETL (Extract, Transform, Load) processes, data pipelines, and data integration solutions.
• Ensure that data engineering solutions align with the organization's long-term data strategy and goals.
• Evaluate and recommend data governance strategies and practices, including data privacy, security, and compliance measures.
• Collaborate with data scientists, analysts, and other stakeholders to define data requirements and enable effective data analysis and reporting.
• Provide technical guidance and expertise to data engineering teams, promoting best practices and ensuring high-quality deliverables.
• Support the team throughout the implementation process, answering questions and addressing issues as they arise.
• Oversee the implementation of the solution, ensuring it conforms to design documents and technical specifications.
• Stay updated with emerging trends and technologies in data engineering, recommending and implementing innovative solutions as appropriate.
• Conduct performance analysis and optimization of data engineering systems, identifying and resolving bottlenecks and inefficiencies.
• Ensure data quality and integrity throughout the data engineering processes, implementing appropriate validation and monitoring mechanisms.
• Collaborate with cross-functional teams to integrate data.

Open-ended freelance agreement requiring active sole proprietorship (B2B) throughout the engagement. Position is remote and part-time with flexible hours.