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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringbackend engineeringPythonPostgreSQLOpenSearchElasticsearchETLELTInfrastructure as Codedistributed systems

Soft Skills

ownershipdecision makingcollaborationadaptabilityproblem solving