Advance your career at Iris Software, recognized as one of India's Top 25 Best Workplaces in IT. We are a rapidly expanding IT services company committed to helping our clients achieve technology-enabled transformation. Join a dynamic environment where your talent is valued, and you can shape your own success story.

Our expertise spans across financial services, healthcare, transportation, and professional services, utilizing cutting-edge technologies in Application & Product Engineering, Data & Analytics, Cloud, DevOps, and more. At Iris, we believe in fostering a culture where your potential is recognized and your contributions make a real impact.

Shape scalable data engineering solutions using PySpark and advanced distributed processing frameworks. Define robust data ingestion, transformation, and processing architectures aligned with business goals.

Design and optimize enterprise-scale data platforms with Snowflake or Delta Lake on Databricks. Lead the development of high-performance batch and streaming data pipelines, and architect event-driven data flows using Apache Kafka or Amazon Kinesis.

Establish standards for data streaming and integration, and architect workflow orchestration with Apache Airflow or Databricks Workflows. Implement comprehensive monitoring, scheduling, and operational controls for reliable pipeline execution.

Drive data quality, validation, and governance practices across all data engineering solutions. Promote the responsible use of AI-assisted engineering to boost productivity and enhance quality.

Review and ensure data pipeline designs and implementations meet rigorous engineering, scalability, and performance standards. Troubleshoot complex data processing and streaming issues through detailed root cause analysis, and mentor team members on best practices.

Possess mandatory skills in PySpark, Apache Kafka, Databricks Workflows, and Delta Lake on Databricks. Experience with Snowflake, Amazon Kinesis, and Apache Airflow is highly desirable.

Demonstrate strong ownership and collaborative spirit in driving data engineering excellence. Apply analytical thinking to tackle complex platform challenges and promote quality-focused engineering through continuous improvement.

Proven ability to design and optimize scalable data solutions, including batch and streaming pipelines. Experience with Lakehouse architecture principles, data observability, and platform engineering standards is expected.

Be proficient in mentoring team members and collaborating with diverse stakeholders for end-to-end data platform delivery. A Bachelor's degree or equivalent in a relevant field is required.