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Job Description
Structured overview of role & requirementsAbout This Role
Design and lead scalable data engineering solutions using PySpark, Apache Kafka, Databricks Workflows, and Delta Lake to support enterprise-scale data platforms.
Architect and optimize batch and streaming data pipelines, event-driven data architectures, and workflow orchestration for reliable and high-performance data platform operations.
Drive data quality, governance, and development of business-focused data products, while mentoring team members and collaborating with stakeholders for end-to-end delivery.
Minimum Requirements
Proficiency in PySpark, Apache Kafka, Databricks Workflows, and Delta Lake on Databricks is mandatory.
Experience with Snowflake or Delta Lake on Databricks and event-driven architectures such as Kafka or Amazon Kinesis required.
Work Experience Required: Not explicitly mentioned in the JD.
Location Requirement: Must be located in or willing to work in Noida, UP, India.
Ideal Candidate Profile
Experienced in designing and implementing modern Lakehouse architecture and data observability practices for scalable and reliable data platforms.
Able to troubleshoot complex data processing and streaming issues with strong analytical thinking and attention to detail.
Capable of mentoring technical teams and collaborating across multiple teams and business stakeholders to ensure smooth delivery and adoption of data engineering best practices.