Principal Data Engineer (Remote)

A global engineering services provider specializing in outstaffing and outsourcing for fast-growing startups and established international companies, with a strong presence in the US and global markets. The client is operating a high-frequency, low-latency OLTP trading system requiring extreme reliability and performance at scale. This is a senior individual contributor role embedded in a lean, high-ownership engineering environment with direct collaboration with founders.

We are looking for a Principal Data Engineer to join a team operating a high-frequency, low-latency OLTP trading system within a leading fintech environment. This is a deep specialist role for someone who lives and breathes database performance, understands the unforgiving demands of high-throughput transactional systems, and can make architectural decisions that hold up under extreme load.

You will own the design, architecture, and optimization of PostgreSQL on AWS RDS, driving performance tuning, indexing strategies, and schema design tailored to low-latency workloads. You will establish and enforce data engineering standards, best practices, and reliability patterns across the platform, and architect scalable data pipelines and storage solutions aligned with high-throughput trading system requirements.

As the internal subject matter expert on all things data infrastructure, you will lead capacity planning, infrastructure scaling, and availability strategies for critical data systems. You will collaborate closely with backend engineers and system architects on data model design, proactively identify and resolve bottlenecks and single points of failure, and contribute to technical documentation, runbooks, and incident response processes.

This is a short-term contractor engagement (4–8 weeks), fully remote, requiring overlap with Central European Time (CET) business hours. The role offers a high level of ownership over production-grade, mission-critical data infrastructure in a demanding, high-performance environment.

• 8+ years of professional data engineering or database engineering experience — required

• Deep expertise in PostgreSQL — required, including advanced query optimization, indexing, partitioning, vacuuming, and replication

• Hands-on experience with PostgreSQL RDS on AWS — required

• Proven background in high-frequency, high-throughput, or low-latency systems (trading, gaming, fintech, or similar domains)

• Strong understanding of OLTP system design, transactional integrity, and concurrency patterns

• Experience with AWS data infrastructure (RDS, Aurora, EC2, CloudWatch, and related services)

• Ability to make and defend architectural decisions independently at the principal level

• Hands-on experience with AI-assisted engineering tools (e.g. AI coding assistants such as Claude Code, Cursor, or similar) — required

• Strong sense of ownership, engineering accountability, and proactive communication

• Good level of spoken and written English: able to communicate complex data topics clearly across distributed teams

• Ability to overlap with Central European Time (CET) working hours

• Ability to start immediately

• Preferred: Experience with order management systems (OMS) or execution management systems (EMS) in a trading context

• Preferred: Familiarity with self-hosted OMS platforms

• Preferred: Experience with time-series databases (e.g. TimescaleDB, InfluxDB) alongside PostgreSQL

• Preferred: Knowledge of data streaming and event-driven architectures (e.g. Kafka, Kinesis)

• Preferred: Familiarity with infrastructure-as-code tools (e.g. Terraform, CDK) for managing AWS data infrastructure

• Preferred: Experience with observability and monitoring tools (e.g. Datadog, Prometheus, Grafana) applied to database performance

• Preferred: Background in regulated financial or fintech environments

• 100% remote engagement with flexible contractor arrangement

• Compensation in USD via a convenient payment method

• Short-term contract engagement (4–8 weeks) with clearly scoped scope of work

• Direct collaboration with founders and fast decision-making — minimal bureaucracy

• High level of ownership over critical, production-grade data infrastructure in a demanding, high-performance fintech environment

• Opportunity to work on a genuinely complex, high-stakes technical problem in a high-frequency trading context