Join Iris Software, a rapidly growing IT services company and a recognized Top 25 Best Workplace in India. We are seeking a Data Senior Engineer to contribute to our award-winning culture and help clients thrive with technology-enabled transformation. Our vision is to be the most trusted technology partner, offering opportunities for top professionals to realize their full potential across financial services, healthcare, transportation & logistics, and professional services.

At Iris, your career is a launchpad for growth. We empower you to "Build Your Future. Own Your Journey." with a culture that values your potential and impact. Through cutting-edge projects, personalized development, and continuous learning, we support your professional and personal evolution.

Design and implement scalable data engineering solutions using PySpark and modern distributed data processing frameworks. Develop robust data ingestion, transformation, and processing architectures aligned with business goals. Optimize Snowflake or Delta Lake on Databricks solutions for enterprise-scale data platforms. Lead the creation of high-performance batch and streaming data pipelines, including event-driven architectures with Apache Kafka or Amazon Kinesis. Establish monitoring, scheduling, and operational controls for reliable pipeline execution and drive data quality, validation, and governance practices. Design data engineering solutions following Lakehouse architecture principles and promote responsible AI-assisted engineering for enhanced productivity.

Review data pipeline designs and implementations to ensure adherence to standards. Troubleshoot complex data processing, workflow, and streaming platform issues through root cause analysis. Mentor team members on PySpark, Snowflake, Delta Lake, Kafka, Kinesis, Airflow, and best practices. Collaborate with various teams and stakeholders for end-to-end data platform delivery.

Mandatory skills include Python, PySpark, Databricks Workflows, Delta Lake on Databricks, and Apache Kafka. Optional skills encompass AWS CloudShell and Azure Databricks. Behavioral competencies include strong ownership, effective collaboration with teams and stakeholders, a quality-focused engineering mindset, and robust analytical thinking to tackle complex platform challenges.

We are looking for individuals who demonstrate strong ownership and drive data engineering excellence. Effective collaboration with business stakeholders is crucial for smooth delivery. A commitment to quality-focused engineering through proactive validation and continuous improvement is expected. Strong analytical thinking is required to evaluate complex data engineering and platform challenges.