Architect

Data Engineering Lead & Architect

Key Responsibilities:

• Lead and mentor a team of data engineers, providing guidance, support, and professional development opportunities.
  
• Develop and implement data engineering strategies that align with the organization’s goals and objectives.
  
• Collaborate with cross-functional teams including data science, analytics, and IT to drive data initiatives.
  
• Design and architect scalable, robust, and secure data pipelines and infrastructure.
  
• Evaluate and select appropriate data technologies and tools to meet the needs of various projects.
  
• Ensure data architecture is optimized for performance, scalability, and reliability.
  
• Oversee data integration, transformation, and loading processes to ensure data accuracy and consistency.
  
• Implement data governance policies and best practices to maintain data quality and security.
  
• Monitor and optimize data storage solutions for efficiency and cost-effectiveness.
  
• Lead data engineering projects from inception to completion, ensuring timely delivery and high quality.
  
• Manage project timelines, resources, and budgets effectively.
  
• Communicate project status, risks, and issues to stakeholders.
  
• Stay current with industry trends and emerging technologies in data engineering and architecture.
  
• Identify opportunities for process improvements and implement innovative solutions.
  
• Foster a culture of continuous learning and development within the data engineering team.
  

Requirements

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
  
• 10+ years of experience in data engineering, with a focus on architecture and leadership roles.
  
• Proven experience with data modeling, ETL processes, and data warehousing solutions.
  
• Strong proficiency in programming languages such as Python, Java, or Scala.
  
• Extensive experience with cloud platforms, particularly Azure.
  
• Expertise with cloud-based data warehouses, especially Snowflake.
  
• Proficiency in using Azure Data Factory (ADF) and Azure Databricks (ADB).
  
• In-depth knowledge of database systems, both SQL and NoSQL.
  
• Excellent problem-solving skills and the ability to troubleshoot complex data issues.
  
• Strong communication and interpersonal skills, with the ability to collaborate effectively with diverse teams.