Join Iris Software, recognized as one of India's Top 25 Best Workplaces in the IT industry, and elevate your career to new heights. As a fast-growing IT services company, we empower our professionals to own and shape their success stories within an award-winning culture that values talent and ambition. Our vision is to be the most trusted technology partner for our clients and the preferred choice for top industry professionals seeking to realize their full potential.

We serve enterprise clients across financial services, healthcare, transportation & logistics, and professional services, delivering complex, mission-critical applications using cutting-edge technologies. Our expertise spans application and product engineering, data & analytics, cloud, DevOps, MLOps, quality engineering, and business automation.

As a Senior ETL Data Engineer, you will architect and implement scalable data engineering solutions using PySpark and modern distributed data processing frameworks. This includes defining data ingestion, transformation, and processing architectures aligned with business objectives. You will design and optimize Snowflake or Delta Lake on Databricks solutions for enterprise-scale data platforms, leading the implementation of high-performance batch and streaming data pipelines.

Your role will involve defining data streaming standards, integration frameworks, and scalable processing patterns, as well as architecting workflow orchestration using Apache Airflow or Databricks Workflows. You will establish robust monitoring, scheduling, and operational controls to ensure reliable pipeline execution and drive data quality, validation, reconciliation, and governance practices. Designing solutions based on Lakehouse architecture principles, data observability, and platform engineering standards will be key to enhancing scalability, reliability, and operational visibility.

We are seeking a Senior ETL Data Engineer with mandatory skills in PySpark, Databricks Workflows, Delta Lake on Databricks, and Amazon Kinesis. Proficiency in designing and optimizing Snowflake or Delta Lake on Databricks solutions is essential. Experience with Apache Airflow or Databricks Workflows for orchestrating batch and streaming pipelines is required.

Candidates should demonstrate strong ownership, effective collaboration with diverse teams and stakeholders, and a commitment to quality-focused engineering through proactive validation and optimization. You should possess strong analytical thinking to tackle complex data engineering and platform challenges, coupled with adaptability in managing evolving technologies and business requirements. Excellent communication skills for reporting status, risks, and dependencies are crucial. A high level of attention to detail in architecture, design, testing, and implementation is expected, alongside a drive for continuous improvement in data engineering practices and platform operations.