Urgent! Cognite - Senior Data Platform Engineer Job Opening In Bengaluru – Now Hiring Cognite
<p><p><b>Job Description : </b></p><p><br/></p><p>Function : Software Engineering Backend Development</p><p><br/><br/>SparkSpark Streaming<br/><br/>Cognite is revolutionising industrial data management through our flagship product, Cognite Data Fusion - a state-of-the-art SaaS platform that transforms how industrial companies leverage their data.
We're seeking a Senior Data Platform Engineer who excels at building high-performance distributed systems and thrives in a fast-paced startup environment.
You'll be working on cutting-edge data infrastructure challenges that directly impact how Fortune 500 industrial companies manage their most critical operational data.<br/><br/><b>Responsibilities : </b><br/><br/>- High-Performance Data Systems : Design and implement robust data processing pipelines using Apache Spark, Flink, and Kafka for terabyte-scale industrial datasets.<br/><br/>- Build efficient APIs and services that serve thousands of concurrent users with sub-second response times.<br/><br/>- Optimise data storage and retrieval patterns for time-series, sensor, and operational data.<br/><br/>- Implement advanced caching strategies using Redis and in-memory data structures.<br/><br/>Distributed Processing Excellence : <br/><br/>- Engineer Spark applications with a deep understanding of Catalyst optimiser, partitioning strategies, and performance tuning<br/><br/>- Develop real-time streaming solutions processing millions of events per second with Kafka and Flink.<br/><br/>- Design efficient data lake architectures using S3/GCS with optimised partitioning and file formats (Parquet, ORC).<br/><br/>- Implement query optimisation techniques for OLAP datastores like ClickHouse, Pinot, or Druid.<br/><br/>- Scalability and Performance : <br/><br/>- Scale systems to 10K+ QPS while maintaining high availability and data consistency.<br/><br/>- Optimise JVM performance through garbage collection tuning and memory management.<br/><br/>- Implement comprehensive monitoring using Prometheus, Grafana, and distributed tracing.<br/><br/>- Design fault-tolerant architectures with proper circuit breakers and retry mechanisms.<br/><br/>Technical Innovation : <br/><br/>- Contribute to open-source projects in the big data ecosystem (Spark, Kafka, Airflow).<br/><br/>- Research and prototype new technologies for industrial data challenges.<br/><br/>- Collaborate with product teams to translate complex requirements into scalable technical solutions.<br/><br/>- Participate in architectural reviews and technical design discussions.<br/><br/><b>Requirements : </b><br/><br/>Distributed Systems Experience (4-6 years) : </p><p><br/></p><p>- Production Spark experience - built and optimised large-scale Spark applications with understanding of internals </p><p><br/></p><p>- Streaming systems proficiency - implemented real-time data processing using Kafka, Flink, or Spark Streaming </p><p><br/></p><p>- JVM Language expertise - strong programming skills in Java, Scala, or Kotlin with performance optimisation experience.<br/><br/>Data Platform Foundations (3+ years) : </p><p><br/></p><p>- Big data storage systems - hands-on experience with data lakes, columnar formats, and table formats (Iceberg, Delta Lake) </p><p><br/></p><p>- OLAP query engines - worked with Presto/Trino, ClickHouse, Pinot, or similar high-performance analytical databases </p><p><br/></p><p>- ETL/ELT pipeline development - built robust data transformation pipelines using tools like DBT, Airflow, or custom frameworks<br/><br/>Infrastructure and Operations : </p><p><br/></p><p>- Kubernetes production experience -deployed and operated containerised applications in production environments.
</p><p><br/></p><p>- Cloud platform proficiency - hands-on experience with AWS, Azure, or GCP data services.</p><p><br/><br/>- Monitoring and observability - implemented comprehensive logging, metrics, and alerting for data systems.<br/><br/><b>Technical Depth Indicators : </b><br/><br/>- Performance Engineering - System optimisation experience - delivered measurable performance improvements (2x+ throughput gains).<br/><br/>- Resource efficiency - optimised systems for cost while maintaining performance requirements.<br/><br/>- Concurrency expertise - designed thread-safe, high-concurrency data processing systems.<br/><br/>- Data Engineering Best Practices - Data quality frameworks -implemented validation, testing, and monitoring for data pipelines.<br/><br/>- Schema evolution - managed backwards-compatible schema changes in production systems.<br/><br/>- Data modelling expertise - designed efficient schemas for analytical workloads.<br/></p><br/></p> (ref:hirist.tech)
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Unlock Your Cognite Senior Potential: Insight & Career Growth Guide
Real-time Cognite Senior Jobs Trends in Bengaluru, India (Graphical Representation)
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Great news! Cognite is currently hiring and seeking a Cognite Senior Data Platform Engineer to join their team. Feel free to download the job details.
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