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Core and Tools Lead

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Onsite

Core and Tools Lead

Automios

Core and Tools Lead

Skills

PythonPostgreSQLMachine LearningAICompliance

1 year ago

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Important information


Contract type:

Permanent

Location:

Chennai, Tamil Nadu, India

Work mode:

Onsite

Published on:

10 September 2026

What they need


JD for Core and tools lead

Key Responsibilities  Architect & Design: Define the technical vision and architecture, ensuring scalability, reliability, and efficiency.

 Performance Optimization: Lead efforts in query optimization, indexing strategies, and efficient data partitioning for distributed workloads.

 Database Internals & Citus Integration: Enhance PostgreSQL and Citus features to improve distributed data processing.

 Replication & High Availability: Design and implement robust replication, failover, and backup strategies.

 Security & Compliance: Ensure data integrity, encryption, and adherence to industry security standards.

 Tooling & Monitoring: Enhance database monitoring tools to improve observability.  Collaboration: Work closely with developers, DevOps, and product teams to align database technology with business needs.

 Research & Innovation: Stay updated with industry trends in distributed databases, cloud-native architectures, and storage engines.

Required Skills & Experience  8 plus years of hands-on experience and strong proficiency in C and C++ for developing database engines.

 Working knowledge of Python and Perl is a plus.

 Experience with query planning, indexing, and database performance tuning.

 Deep understanding of replication, sharding, and high-availability architectures.

 Hands-on experience with PostgreSQL performance monitoring tools.

 Experience in database security, access control, and encryption.

 Strong problem-solving skills and the ability to mentor engineering teams.

Preferred Qualifications  Contributions to PostgreSQL, Citus, or open-source database projects.

 Knowledge of distributed consensus algorithms (Raft, Paxos).

 Experience in parallel query execution.

 Exposure to AI/ML-driven database optimizations.

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