Job Title: Senior Staff Engineer-Data Platform
Experience: 13–15 Years
Location: Bengaluru - Hybrid
About the Company:
Our client is a global leader in cloud security, offering advanced solutions that protect data, users, and applications across cloud and web environments. It focuses on enabling secure digital transformation through visibility, threat prevention, and data protection. The company’s innovative platform supports a zero-trust approach and helps enterprises maintain compliance while improving productivity. It’s known for a strong culture of innovation, collaboration, and employee growth.
Role Overview:
The Data Platform team is uniquely positioned at the intersection of security, big data, and cloud computing. We are responsible for providing ultra low-latency access to global security insights and intelligence data to our customers, enabling them to act in near real-time. We’re looking for a seasoned Backend Engineer with strong distributed systems experience and mandatory Data Platform architecture expertise to help us build next-generation data pipelines that provide near real-time ingestion of security insights and intelligence data using cloud and open-source data technologies.
Key Responsibilities:
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.
Required Skills:
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.
Eligibility / Qualifications:
Education: BSCS or equivalent required, MSCS or equivalent strongly preferred
Other Details:
Notice Period: Immediate to 30 days
Work Type: Full-time / Remote