Founding Data Engineer – PG, Opensearch

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Neuroscale AI

Site WebLinkedInTous les Emplois

11 - 50 employés

Fondée en 2024

🤖 Intelligence artificielle

Artificial Intelligence

Neuroscale AI est une entreprise spécialisée dans l'intelligence artificielle. Aucune information supplémentaire n'ayant été fournie, cette description se base uniquement sur le nom et suggère une spécialisation dans les technologies, la recherche ou les produits liés à l'intelligence artificielle.

Description

• Design, build, and maintain scalable batch and streaming data pipelines that support Neuroscale AI's core platform • Build robust ingestion, transformation, enrichment, and indexing workflows across structured, semi-structured, and document-centric data • Develop and operate production-grade data systems using PostgreSQL, OpenSearch/Elasticsearch, AWS, and Python-based tooling • Design efficient data models, schemas, and storage patterns that support analytics, search, application workflows, and AI use cases • Build secure cloud-native data infrastructure using AWS services such as S3, Lambda, Glue, Kinesis, and IAM • Optimize PostgreSQL for advanced SQL workloads, replication, query performance, and data integrity • Design and manage search and retrieval pipelines in OpenSearch/Elasticsearch for high-speed, relevant access to data • Improve observability, lineage, testing, and reliability across the data platform • Automate infrastructure provisioning and environment management using Terraform or CloudFormation • Partner closely with backend, product, and AI teams to enable new data-driven capabilities and platform features • Help define engineering standards, data platform best practices, and operational playbooks as the company scales

🎯 Exigences

• Strong experience in data engineering or backend/data platform engineering in production environments • Strong programming skills in Python; experience with Typescript is a plus • Deep hands-on experience with PostgreSQL, including advanced SQL, schema design, query tuning, indexes, sharding, replication, and modeling • Strong experience with OpenSearch/Elasticsearch, including indexing strategy, search performance, relevance tuning, and distributed query operations at very large scale • Experience building and maintaining ETL/ELT pipelines and data processing workflows for large-scale datasets • Hands-on experience with AWS data and infrastructure services, especially S3, Lambda, Glue, Kinesis, and IAM • Experience designing reliable cloud-native data architectures and secure data movement patterns • Experience with Infrastructure as Code, ideally Terraform or CloudFormation • Strong understanding of distributed systems, production operations, fault tolerance, and data reliability • Ability to work with high ownership, move quickly, and make sound engineering decisions in a startup environment

🏖️ Avantages

• Base Salary: $100,000 – $200,000 • Equity: ~0.1–0.75% early-stage equity with a clear range shared during the process • Bonus: Quarterly performance bonuses tied to clear feature shipping targets • Healthcare: Medical, dental, and vision coverage • PTO: 14 days accrued annually • Learning: $2,000+ per year for courses, conferences, books, and communities • Equipment: New MacBook Pro, monitor, and a monthly tools budget • Flexibility: Flexible hours; ideally in-person in the Northern Virginia / Washington DC region (remote considered) • Growth: Clear, fast-track path to Engineering Lead as the team scales