Senior Data Engineer (Remote)

Job summary

This fully remote position is for an experienced Senior Data Engineer to contribute to a large-scale digital transformation initiative. The role involves designing, developing, and maintaining scalable data solutions that provide reliable, analytics-ready information across the organization, with a strong emphasis on the Microsoft Azure data ecosystem.

Qualifications

• Minimum of 5 years of hands-on experience with Python and SQL in a data engineering context.
• At least 3 years of experience with Azure services, including Azure Storage, Azure SQL, Azure Synapse, and Azure networking.
• Proven experience with Azure Databricks and Delta Lake for at least 3 years.
• Experience in designing data solutions and developing trusted, analytics-ready datasets for at least 3 years.
• At least 4 years of experience with version control systems, particularly Git.
• At least 1 year of practical experience using AI tools for data engineering tasks.
• Strong understanding of data engineering principles, ETL/ELT processes, and data pipeline development.
• Advanced SQL development and data transformation skills.
• Excellent analytical and problem-solving abilities.
• Strong communication and collaboration skills.
• Ability to work independently in a remote environment.

Responsibilities

• Design, develop, and maintain scalable data solutions for a digital transformation program.
• Build and optimize ETL/ELT pipelines integrating diverse data sources into analytics-ready datasets.
• Develop cloud-based data solutions using the Microsoft Azure ecosystem.
• Use Python and SQL for data transformations and processing workflows.
• Manage data models and architectures for scalability and performance.
• Collaborate with stakeholders to translate requirements into effective data engineering solutions.
• Apply version control and engineering best practices using Git.
• Troubleshoot technical issues and optimize data workflows.

Skills

• Proficiency in Python and SQL.
• Experience with Azure services and cloud-based data platforms.
• Familiarity with AI-powered tools for data engineering.
• Strong analytical and problem-solving skills.

Education

• Relevant educational background in computer science, data engineering, or a related field is preferred.

Tools

• Microsoft Azure services (Data Factory, Databricks, Synapse Analytics, Data Lake Storage Gen2).
• Python, SQL, Delta Lake, Git.