Join Iris Software, a recognized "Great Place to Work" and one of India's fastest-growing IT services companies. We are seeking a Senior Data Engineer to contribute to cutting-edge projects. At Iris, we empower our associates with ownership and provide a launchpad for professional growth, supported by a culture that values talent and ambition. Our vision is to be the premier technology partner for enterprises, driving transformation across financial services, healthcare, transportation & logistics, and professional services using advanced technologies like Data & Analytics, Cloud, and DevOps.

Our commitment to our employees is captured in our Employee Value Proposition: “Build Your Future. Own Your Journey.” We offer personalized career development, continuous learning, and mentorship to help you achieve your full potential. Discover the vibrant culture and exciting opportunities at Iris Software through our "Inside Look" video.

As a Senior Data Engineer, you will be instrumental in designing and implementing scalable data engineering solutions. This includes developing robust data ingestion, transformation, and processing architectures using PySpark and distributed frameworks. You will architect and optimize Snowflake or Delta Lake on Databricks solutions for enterprise-scale data platforms. Key responsibilities also involve leading the implementation of high-performance batch and streaming data pipelines, designing event-driven architectures with Apache Kafka or Amazon Kinesis, and establishing comprehensive monitoring and operational controls.

You will drive data quality, validation, and governance initiatives, ensuring adherence to modern Lakehouse architecture principles and platform engineering standards. Promoting the responsible use of AI-assisted engineering to enhance productivity and quality is also a core aspect of this role. You will mentor team members, collaborate with stakeholders for end-to-end platform delivery, and troubleshoot complex data processing issues through root cause analysis. Ensuring adherence to engineering, scalability, and performance standards through design reviews is essential.

We are looking for a Senior Data Engineer with 7-8 years of experience, proficient in mandatory skills such as Amazon Kinesis, Apache Spark, Data Quality & Validation, PySpark, SQL, Apache Airflow, and Delta Lake on Databricks. Experience with Snowflake is also required.

Additional skills in Python and basic DevOps & CI/CD are beneficial. You should demonstrate strong ownership, collaboration, and analytical thinking. Adaptability to evolving technologies and excellent communication skills are vital. A high attention to detail in data architecture, pipeline design, and implementation is expected. Balancing scalability, performance, reliability, and business priorities is key to success in this role. We encourage candidates to promote innovation and continuous improvement in data engineering practices.