Data Engineer

Infosys Consulting is the worldwide management and IT consultancy unit of the Infosys Group (NYSE: INFY), a global advisor to leading companies for strategy, process engineering and technology-enabled transformation programs. We partner with clients to design and implement customized solutions to address their complex business challenges, and to help them in a post-modern ERP world. By combining innovative and human-centric approaches with the latest technological advances, we enable organizations to reimagine their future and create sustainable and lasting business value. A pioneer in breaking down the barriers between strategy and execution, Infosys Consulting delivers superior business value to its clients by advising them on strategy and process optimisation as well as IT-enabled transformation. To find out how we go beyond the expected to deliver the exceptional, visit us at www.infosysconsultinginsights.com.

We are seeking a highly skilled Data Engineer with strong expertise in the AWS ecosystem to design, develop, and maintain scalable data platforms and pipelines. The ideal candidate will have advanced SQL capabilities, experience with modern data engineering practices, Python, CI/CD implementation, Databricks, MLOps concepts, and reporting tools such as Power BI or Tableau.

This role requires collaboration with data scientists, analysts, software engineers, and business stakeholders to deliver robust data solutions that support analytics, reporting, and machine learning initiatives.

• →Design, build, and optimize scalable data pipelines and ETL/ELT processes using AWS services.
• →Develop and maintain data models, data warehouses, and lakehouse architectures.
• →Write, optimize, and troubleshoot complex SQL queries for data extraction, transformation, and analysis.
• →Build and automate deployment processes using CI/CD best practices, preferably with GitHub and GitHub Actions.
• →Develop data processing solutions using Python (preferred) or Java.
• →Work with Databricks to process large-scale datasets and support advanced analytics workloads.
• →Collaborate with Data Science teams to support machine learning workflows and MLOps practices.
• →Monitor, maintain, and improve data quality, reliability, and performance.
• →Create and support reporting solutions using Power BI, Tableau, or other BI platforms.
• →Implement data governance, security, and compliance standards across data platforms.
• →Participate in architecture discussions and provide recommendations for scalable cloud-based data solutions.