Join Iris Software, a rapidly growing IT services company recognized among India's Top 25 Best Workplaces in the IT industry. We are committed to being a trusted technology partner and a top choice for professionals seeking to realize their full potential. With a global presence across India, the U.S.A., and Canada, we empower enterprise clients in financial services, healthcare, transportation & logistics, and professional services through technology-enabled transformations.

Our expertise spans complex, mission-critical applications leveraging cutting-edge technologies such as Application & Product Engineering, Data & Analytics, Cloud, DevOps, Data & MLOps, Quality Engineering, and Business Automation. At Iris, we believe in empowering our associates with ownership and providing a launchpad for career growth, fostering a culture where potential is valued, voices matter, and work creates real impact.

As a Senior Data Engineer, you will be instrumental in designing and implementing scalable data engineering solutions. This includes creating robust ingestion, transformation, and processing architectures using PySpark and modern distributed frameworks. You will architect and optimize Snowflake or Delta Lake on Databricks solutions, and lead the development of high-performance batch and streaming data pipelines.

Key responsibilities involve designing event-driven architectures with Apache Kafka or Amazon Kinesis, establishing data streaming standards, and architecting workflow orchestration using Apache Airflow or Databricks Workflows. You will also ensure reliable pipeline execution through monitoring and scheduling, drive data quality and governance, and promote the responsible use of AI-assisted engineering for enhanced productivity and quality. Mentoring team members and collaborating with stakeholders are also integral parts of this role.

We are seeking candidates with mandatory skills in PySpark, Apache Kafka, Databricks Workflows, and Delta Lake on Databricks. A strong foundation in designing scalable data engineering solutions and modern Lakehouse architecture principles is essential.

Ideal candidates demonstrate strong ownership, effective collaboration, and a quality-focused engineering approach. Excellent analytical thinking, adaptability to evolving technologies, and clear communication regarding delivery status, risks, and improvements are expected. A high level of attention to detail across data architecture, pipeline design, and implementation is crucial. While not explicitly stated, a Bachelor's degree in a relevant field is generally expected for this senior-level position.