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.

EducationBachelor’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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