Principal Engineer - Data Platform
Description
- You will be part of a growing team of renowned industry experts in the exciting space of Data and Cloud Analytics.
- Your contributions will have a major impact on our global customer base and across the industry through our market-leading products.
- You will solve complex, interesting challenges and improve the depth and breadth of your technical and business skills.
- Build next-generation data pipelines for near real-time ingestion of security insights and intelligence data.
- Design, architect, and scale distributed backend systems that power high-throughput, low-latency data platforms.
- Drive Data Platform architecture initiatives leveraging technologies such as Snowflake, BigQuery, Databricks, and modern data lake ecosystems.
- Partner with industry experts in security, big data, product, and engineering teams to conceptualize, design, and build innovative solutions for complex customer problems.
- Evaluate open-source technologies to identify the best fit for platform needs and contribute to relevant ecosystems where applicable.
- Collaborate with other teams to architect their systems on top of the data platform and influence overall system architecture and best practices.
- Strong Backend Engineering background with hands-on experience building and scaling distributed systems.
- Mandatory experience in Data Platform architecture and large-scale data infrastructure design.
- Hands-on exposure to Big Data technologies such as Hadoop, Kafka, and modern data lake architectures.
- Expertise in architecting and designing highly scalable, efficient, and fault-tolerant data pipelines for near real-time and real-time processing.
- Experience with Data Platform technologies such as Snowflake, BigQuery, and Databricks.
- Strong diagnostic and problem-solving skills with a demonstrated ability to simplify complex systems into elegant solutions.
- Cloud-native data infrastructure experience with AWS, GCP, or similar cloud platforms is a strong plus.
- Solid understanding of distributed object storage systems (e.g., S3, GCS), their architectures, consistency models, and scaling characteristics.
- Good to have experience in designing high-throughput, low-latency data services; experience with gRPC/RPC is a plus.
- Deep understanding of data formats such as Parquet and Iceberg, including partitioning, sorting, compression, and read performance optimization.
- Expert-level proficiency in Golang, Java, or similar languages with a strong understanding of concurrency, distributed computing, and system-level optimizations.
- Proven ability to influence technical direction and communicate with clarity.
- Willingness to work with a globally distributed team across different time zones.
