Founding Data Engineer – PG, Opensearch
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Job Description
Founding Data Engineer responsible for building the data infrastructure at Neuroscale AI. Designing and maintaining scalable data systems to support AI-driven products.
Responsibilities:
- 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
Requirements:
- 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
Benefits:
- 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
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