Data Platform Engineer

We are looking for a Data Platform Engineer to design, build, and scale high-performance distributed data platforms. The ideal candidate will have strong experience in distributed systems, large-scale data infrastructure, Cassandra, and system architecture. This is a highly technical role for engineers who have architected and built scalable production systems, rather than primarily working on traditional ETL or data pipelines.
Responsibilities:
Design and architect highly scalable, distributed data platforms and systems.
Build reliable, fault-tolerant systems capable of handling large data volumes and high throughput.
Work extensively with Cassandra, including data modeling, partitioning, replication, consistency, performance optimization, and scaling.
Design distributed services and storage systems with a strong focus on availability, scalability, latency, and reliability.
Work with technologies such as Kafka, Spark, Flink, Redis, Elasticsearch, or similar distributed data technologies.
Identify and solve complex problems related to distributed computing, data consistency, replication, partitioning, and fault tolerance.
Drive architectural decisions and contribute to technical design and engineering best practices.
Collaborate with other engineering teams to build robust data infrastructure and platform capabilities.
Requirements:
We are looking for engineers from top-tier product companies, high-growth technology companies, or large-scale platforms who have personally contributed to or owned the architecture of distributed systems.
Experience: 5+ years preferred
Must-Have Skills:
Strong experience in distributed systems and large-scale backend/data platforms.
Proven experience architecting and designing distributed systems.
Strong hands-on experience with Apache Cassandra.
Deep understanding of Cassandra data modeling, partitioning, replication, consistency, and performance.
Experience building and operating high-scale production systems.
Strong programming skills in at least one of Java, Go, Python, or C++.
Strong understanding of system design, scalability, fault tolerance, and high availability.
Good to Have:
Experience with Kafka / Spark / Flink / Redis / Elasticsearch / DynamoDB / Bigtable.
Experience with streaming or real-time data platforms.
Experience handling millions/billions of records or high-throughput workloads.
Experience working on infrastructure or platform teams.

Experience
6-10 yrs