Data Engineer - Senior

This is a remote opportunity for an experienced data engineer to play a key role in a large-scale digital transformation initiative. You will design, develop, and maintain scalable data solutions that support reliable, analytics-ready information across the organization. Working closely with business stakeholders, product owners, architects, and technical teams, you will help turn diverse data sources into trusted and usable datasets. The role has a strong focus on the Microsoft Azure data ecosystem and modern cloud-based data architectures. You will work extensively with Azure Data Factory, Databricks, Synapse Analytics, Data Lake Storage Gen2, Python, SQL, and Delta Lake. This is an environment where strong engineering practices, problem-solving, and data quality directly contribute to business and technology outcomes. Accountabilities

• Design, develop, and maintain scalable, reliable data solutions supporting a large-scale digital transformation program.
• Build and optimize robust ETL/ELT pipelines that integrate data from diverse sources into trusted, analytics-ready datasets.
• Develop cloud-based data solutions using the Microsoft Azure ecosystem, including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure SQL, and related services.
• Use Python and SQL to develop data transformations, processing workflows, integrations, and analytical data solutions.
• Design and manage data models and architectures that support scalability, reliability, performance, and data quality.
• Work extensively with Azure Databricks and Delta Lake to build and optimize modern data processing and storage solutions.
• Collaborate with business stakeholders, product owners, data architects, and technical teams to understand requirements and translate them into effective data engineering solutions.
• Apply version control and engineering best practices using tools such as Git to support maintainable, collaborative development.
• Leverage AI-powered tools where appropriate for code generation, data analysis, automation, optimization, and other data engineering activities.
• Troubleshoot technical issues, optimize data workflows, and continuously improve pipeline performance, reliability, and maintainability.
• Communicate technical concepts clearly and contribute to effective collaboration across business and technical teams., * Opportunity to contribute to a large-scale digital transformation initiative with significant data engineering scope.
• Work with a modern Microsoft Azure cloud data ecosystem and widely used data engineering technologies.
• Exposure to advanced platforms and tools including Azure Databricks, Delta Lake, Azure Synapse, Azure Data Factory, Python, and SQL.
• Opportunity to apply AI-powered engineering tools to improve development, automation, analysis, and optimization.
• Collaboration with multidisciplinary teams including business stakeholders, product owners, data architects, and technical specialists.
• Opportunity to work on scalable, production-focused data solutions with direct business impact.
• Remote working environment designed to support autonomy and flexibility.

• At least 5 years of hands-on experience with Python and SQL in a data engineering environment.
• At least 3 years of experience working with Azure services, including Azure Storage, Azure SQL, Azure Synapse, and Azure networking.
• At least 3 years of hands-on experience with Azure Databricks and Delta Lake.
• At least 3 years of experience designing data solutions and developing trusted, analytics-ready datasets.
• At least 4 years of experience with version control systems, particularly Git.
• At least 1 year of practical experience using AI tools for code generation, data analysis, automation, optimization, or related data engineering tasks.
• Strong understanding of data engineering principles, ETL/ELT processes, data integration, and data pipeline development.
• Advanced SQL development and data transformation capabilities.
• Proven experience working with cloud-based data platforms and modern data architectures.
• Strong analytical and problem-solving abilities, with a structured approach to diagnosing and resolving complex technical challenges.
• Excellent communication and collaboration skills, with the ability to work effectively with both technical teams and business stakeholders.
• Ability to work independently in a remote environment while maintaining strong ownership, organization, and delivery focus.