ETL Developer en Nutanix

Hungry, Humble, Honest, with Heart.

The Opportunity

We are looking for a highly skilled Data Integration Engineer to design, build, and manage scalable data pipelines and integration solutions across cloud and on-premises platforms. The role requires strong expertise in ETL/iPaaS tools, APIs, and data platforms, with exposure to AI/ML-driven automation for smarter monitoring, anomaly detection, and data quality improvement.

About the Team

At Nutanix, the Data Science team is a dynamic and diverse group of 50 talented professionals spread across our offices in India (Bangalore and Pune) and San Jose. We pride ourselves on fostering a collaborative and supportive environment where innovation thrives. Our team is deeply committed to leveraging data in a results-oriented manner, ensuring our solutions remain customer-centric. We believe in transparency and trust, which allows for open communication and a fluid exchange of ideas. Being agile and adaptable, we embrace diverse perspectives to drive creativity and efficient problem-solving.

Your Role

• Design, develop, and optimize data integration workflows, ETL/ELT pipelines, and APIs.
• Work with iPaaS and ETL tools (Informatica) to integrate enterprise systems.
• Build pipelines across cloud platforms (AWS, Azure, GCP) and modern warehouses (Snowflake, Databricks, BigQuery, Redshift).
• Implement data quality, lineage, and governance frameworks to ensure reliable data flow.
• Leverage AI/ML models for data anomaly detection, pipeline monitoring, and predictive quality checks.
• Contribute to self-healing pipeline design by incorporating AI-driven automation.
• Collaborate with architects, analysts, and business teams to integrate structured, semi-structured, and unstructured data sources.
• Document integration patterns, best practices, and reusable frameworks.
   
  
   

What You Will Bring

• 6–8 years of experience in data integration, ETL/ELT design, and data pipelines.
• Strong expertise in Informatica, or similar ETL/iPaaS tools.
• Proficiency in SQL, Python, and automation scripting.
• Experience with cloud data platforms (Snowflake, Databricks, BigQuery, etc.).
• Familiarity with data governance practices (cataloging, lineage, DQ frameworks).
• Exposure to AI/ML concepts applied to data quality and pipeline optimization.
• Understanding of DevOps/CI-CD pipelines for data integration deployments.

Nice-to-Have

• Hands-on experience with Kafka, Spark, Airflow, or event-driven architectures.
• Knowledge of REST APIs, microservices, and real-time data integration.
• Conceptual understanding or hands-on exposure to ML frameworks (Scikit-learn, TensorFlow, PyTorch).
• Experience contributing to AI-augmented/self-healing pipelines.
  
  Education
• Bachelor’s or Master’s in Computer Science, Data Engineering, Information Systems, or related field
   

Work Arrangement

Hybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in-person collaboration. For most roles, that will mean coming into an office a minimum of 3 days per week, however certain roles and/or teams may require more frequent in-office presence. Additional team-specific guidance and norms will be provided by your manager.

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