Senior Data Engineer in India at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer based in India.

Join a forward-thinking data engineering team driving digital transformation through scalable, AI-ready data platforms and advanced analytics solutions. In this role, you will design and build modern data architectures that enable intelligent applications, improve operational efficiency, and unlock valuable business insights. You will collaborate with data scientists, analysts, and business stakeholders to create reliable data pipelines and innovative solutions using cloud technologies. Working in a remote environment, you will contribute to high-impact projects that support scientific and operational advancements. This opportunity is ideal for an experienced data engineer passionate about cloud platforms, automation, data governance, and leveraging technology to create meaningful impact.

• Design, develop, and maintain scalable data pipelines and ETL processes using Azure Data Factory, Azure Databricks, and other Azure cloud services.
• Build and optimize data storage solutions using Azure Data Lake, Azure SQL Database, Delta Lake, and related technologies to support analytics, reporting, and AI-driven applications.
• Collaborate with data scientists, analysts, engineers, and business stakeholders to understand requirements and deliver accurate, reliable, and high-quality datasets.
• Implement data security, governance, and compliance practices, including role-based access control, encryption, auditing, and monitoring standards.
• Monitor, troubleshoot, and optimize data workflows to ensure performance, reliability, scalability, and cost efficiency across cloud environments.
• Automate data integration and transformation processes using Azure Functions, Logic Apps, Python, SQL, and other scripting tools.
• Design and implement data models aligned with business requirements and analytics objectives.
• Mentor junior engineers, share technical expertise, and contribute to a collaborative and innovative engineering culture.
• Support the development of AI and machine learning capabilities by enabling robust data foundations and scalable infrastructure.

• Bachelor’s degree in Computer Engineering, Computer Science, or a related technical discipline.
• 7+ years of experience designing, developing, and optimizing ETL solutions using Microsoft data technologies in enterprise data warehousing environments.
• Advanced SQL programming expertise, including PL/SQL and T-SQL.
• 5+ years of experience designing enterprise data and analytics solutions.
• 3+ years of professional experience with Python programming for data engineering or automation tasks.
• 3+ years of hands-on experience with Azure cloud services for data-intensive applications, analytics platforms, data warehousing, and big data solutions.
• Strong experience with Azure services including Azure Data Factory, Azure Data Lake Gen2, Databricks, Blob Storage, SQL Database, Cosmos DB, Analysis Services, App Service, Logic Apps, and Azure Functions.
• Experience designing data models, implementing data security standards, and supporting enterprise data governance initiatives.
• Strong analytical thinking, problem-solving abilities, and curiosity for learning new technologies.
• Preferred experience includes DevOps practices, CI/CD pipelines, infrastructure as code, Master Data Management, data quality tools, REST API development, machine learning solutions, streaming technologies, Agile methodologies, and experience in life sciences or healthcare data environments.

• Fully remote work opportunity from India with flexible home office arrangements.
• Opportunity to contribute to large-scale digital transformation and AI-driven data initiatives.
• Work on advanced cloud technologies and enterprise-level data platforms.
• Collaborate with global teams across engineering, analytics, and business functions.
• Strong opportunities for professional growth, technical development, and knowledge sharing.
• Opportunity to build solutions that support innovation in healthcare and life sciences.
• Supportive environment focused on continuous learning, collaboration, and impactful work.