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# Database/Python Generalist

- **Company:** Castelion Corporation
- **Location:** Allen, TX, United States
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Algorithm Design, Automation of Tests, Databases, Data Infrastructure, Data Security, Data Sharing, Data Systems, Database Models, Python (Programming Language), PostgreSQL, Machine Learning, Query Optimization, SQL Databases, Data Ingestion, Indexer, Backend, Pagination, Data Pipelines, Database Tools and Utilities
- **Published:** October 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=257d49fdb25922da

## About the Role

* Strong Python software engineering skills, including experience building production services and APIs.
 * Demonstrated experience architecting PostgreSQL schemas for real-world applications and safely modifying production databases.
 * Deep PostgreSQL expertise, including indexing, query planning, transactions, locking, and performance analysis.
 * Experience using EXPLAIN and EXPLAIN ANALYZE to optimize real-world query patterns.
 * Experience designing safe schema migrations, backfills, and concurrent index changes.
 * Experience building reliable data-ingestion pipelines and multi-database synchronization systems.
 * Experience with ORMs and direct SQL, with sound judgment about when to use each.
 * Understanding of partitioning, batching, pagination, and efficient bulk reads and writes.
 * Experience developing shared Python types, database models, and reusable data-access tools.

Preferred Skills and Experience

 * Experience automating data-retention, archival, and deletion policies.
 * Experience building calibration, test automation, or engineering data-management systems.
 * Familiarity with hardware-facing Python test systems and chamber testing.
 * Experience supporting algorithm development, machine learning, or other data-intensive engineering workflows.
 * Experience designing dependency-aware data pipelines and systems that select the correct data products automatically.
 * Ability to improve existing systems through targeted, measurable changes while maintaining reliability.

## Description

Castelion is seeking a Database / Python Generalist to build and improve the Seeker Team's calibration automation tooling, PostgreSQL infrastructure, and Python backend services. This role will make far-field calibration faster, more reliable, and easier to execute while enabling engineering teams to access the correct calibration data automatically.

You will work across database architecture, query optimization, data pipelines, and hardware-facing test systems, partnering with algorithm, ML, and test teams to improve existing systems and build scalable solutions. This is a hands-on engineering role focused on practical improvements that directly accelerate seeker development and testing.

Responsibilities

 * Own calibration automation: Develop far-field calibration tooling that combines individual tests into an end-to-end suite runner with resume-from-failure capabilities.
 * Build calibration data infrastructure: Develop Golden Calibration data systems and a Calibration Dependency Graph to support reliable, automated calibration workflows.
 * Optimize PostgreSQL performance: Improve schemas, queries, indexes, partitioning, and data access patterns to accelerate calibration data products and visualization.
 * Evolve database architecture: Design schemas, ORM models, and shared data types to support new requirements from algorithm and ML teams.
 * Build reliable data pipelines: Develop ingestion and synchronization workflows with appropriate retry, idempotency, consistency, and conflict-handling strategies.
 * Maintain production databases safely: Implement schema migrations, backfills, indexing changes, and data-retention, archival, and deletion policies.
 * Develop Python services: Build and maintain production backend services, APIs, database utilities, and reusable data-access components.
 * Support hardware-facing testing: Contribute to Python-based test systems and chamber-testing workflows to expand testing capacity and reduce calibration runtime.
 * Improve existing systems pragmatically: Identify bottlenecks, implement targeted improvements, and avoid unnecessary redesigns.