Role Overview:

We are seeking an experienced Data Engineer to design, build, and maintain scalable data processing and integration solutions across AWS and Azure cloud environments.

The role focuses on developing robust ETL pipelines, ensuring high data quality, and supporting cloud-based data architecture and migration initiatives. The successful candidate will collaborate closely with analysts, business stakeholders, and technical teams to deliver reliable and efficient data solutions.

Scope:

• Design, implement, and maintain scalable data processing solutions in AWS and Azure environments
• Build and optimize ETL pipelines and data integration workflows
• Develop and manage data pipelines using tools such as Azure Data Factory, Synapse, and Databricks
• Ensure data quality, security, and compliance across all data solutions
• Collaborate with business analysts and cross-functional teams to deliver data-driven solutions
• Support data architecture improvements and cloud migration initiatives
• Monitor and optimize performance of data pipelines and systems

Skills:

• 4–6 years of experience in Data Engineering (ETL, data integration, data modeling)
• Strong experience with AWS and/or Azure cloud platforms, including tools such as:
  – Azure Databricks, Data Lake, Data Factory, Synapse
  – AWS Glue, Redshift
  – Snowflake (nice to have)
• Strong proficiency in Python and SQL
• Good understanding of CI/CD pipelines and basic DevOps principles
• Solid knowledge of data integration and data quality best practices
• English level: B2 or higher

Nice to Have:

• Experience in healthcare, fintech, or pharmaceutical projects
• Exposure to large-scale cloud migration programs
• Knowledge of data architecture design and best practices

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