Posted on: 02/09/2026
Role Overview :
As a Senior Data Engineer, you will be the cornerstone of our client's GCP-based data platform, responsible for architecting robust pipelines and ensuring the seamless flow of high-volume data. You will collaborate closely with cross-functional teams, including product managers and data scientists, to translate complex business requirements into high-performance technical solutions. Your work will directly impact the reliability and accessibility of data, enabling stakeholders to make informed, real-time decisions that drive business growth.
Key Responsibilities :
- Develop and optimize complex batch and real-time data pipelines using Spark and PySpark to ensure high data availability and integrity.
- Integrate Kafka into existing data ecosystems to facilitate low-latency streaming and event-driven data ingestion.
- Collaborate with engineering teams to refine data models and improve query performance, ensuring the platform meets evolving business demands.
- Maintain high standards of code quality and system reliability by implementing rigorous testing and monitoring protocols across the data lifecycle.
Required Skillset :
- Strong proficiency in Python or Java, with a deep understanding of Data Structures and Algorithms (DSA) to write efficient, production-grade code.
- Proven ability to design complex batch and streaming data architectures using Spark, PySpark, and Kafka.
- Excellent problem-solving skills with the ability to translate ambiguous business requirements into structured technical specifications.
- Strong communication skills, enabling effective collaboration with both technical peers and non-technical stakeholders in a hybrid work environment.
- Minimum of 6 to 9 years of professional experience in data engineering or a closely related software engineering domain.
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Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1668059