Database Engineer & DBA

System Soft Technologies; Bala Cynwyd (PA); On-site; USD 120,000 - 180,000; Full time

Job summary

System Soft Technologies is seeking an engineer with a strong foundation in database technologies and systems engineering for high-performance, low-latency trading platforms. You will work on application database engineering for front-office environments and collaborate across disciplines to drive performance and reliability.

The role focuses on database design, deployment, and optimization across relational and non-relational systems, with Python tooling and Kubernetes-based workloads.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, or a related field.
• 1-5 years of experience in database engineering, systems engineering, or a related discipline.
• Strong proficiency in SQL and deep working knowledge of relational databases - complex query manipulation, indexing, partitioning, replication, and high availability.
• Solid Python development skills - able to write production-quality scripts and tooling, not just one-off automation.
• Good understanding of Kubernetes - deploying, managing, and debugging containerized workloads.
• Strong Linux fundamentals - shell scripting, process management, system monitoring, and core command-line fluency.
• Comfort operating in a production environment - you handle pressure well and take ownership of reliability.
• Working knowledge of AI tools and best practices for engineering workflows.

Responsibilities

• Design, deploy, and maintain relational and non-relational database systems at scale (hundreds of millions to billions of records, TB-scale datasets), including MongoDB, InfluxDB, and ClickHouse.
• Optimize query performance through advanced indexing strategies, execution plan analysis, and schema design.
• Develop Python tooling and automation to support database operations, maintenance workflows, and system health.
• Ensure high availability and reliability through replication, failover design, and disaster recovery planning.
• Operate confidently in production environments - diagnosing and resolving time-sensitive issues with composure and precision.
• Manage and scale containerized database workloads using Kubernetes, including ClickHouse deployments.
• Monitor system health using observability tooling and proactively address performance degradation.
• Collaborate with developers, researchers, and platform engineers to support data-intensive applications.
• Apply AI tooling and best practices to accelerate engineering workflows.

Skills

SQL

Python

Kubernetes

Linux

AI tooling

Collaboration

Education

Bachelor's degree in CS/IS or related field

Tools

MongoDB

InfluxDB

ClickHouse

Prometheus

Grafana

Terraform

Job description

Our Production Services Team is looking for a skilled engineer with a strong foundation in database technologies and systems engineering , not a traditional DBA, but someone who understands how databases fit into broader system architecture and can collaborate across disciplines to drive performance, reliability, and scalability.

This role is part of a front office support team, focused on application database engineering for trading platforms and directly supporting traders in a high-performance, low-latency environment.

Responsibilities

• Design, deploy, and maintain relational and non-relational database systems at scale (hundreds of millions to billions of records, TB-scale datasets), including MongoDB, InfluxDB, and ClickHouse.
• Optimize query performance through advanced indexing strategies, execution plan analysis, and schema design.
• Develop Python tooling and automation to support database operations, maintenance workflows, and system health.
• Ensure high availability and reliability through replication, failover design, and disaster recovery planning.
• perate confidently in production environments - diagnosing and resolving time-sensitive issues with composure and precision.
• Manage and scale containerized database workloads using Kubernetes, including ClickHouse deployments.
• Monitor system health using observability tooling and proactively address performance degradation.
• Collaborate with developers, researchers, and platform engineers to support data-intensive applications.
• Apply AI tooling and best practices to accelerate engineering workflows.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, or a related field - or equivalent practical experience.
• 1-5 years of experience in database engineering, systems engineering, or a related discipline.
• Strong proficiency in SQL and deep working knowledge of relational databases - complex query manipulation, indexing, partitioning, replication, and high availability.
• Solid Python development skills - able to write production-quality scripts and tooling, not just one-off automation.
• Good understanding of Kubernetes - deploying, managing, and debugging containerized workloads.
• Strong Linux fundamentals - shell scripting, process management, system monitoring, and core command-line fluency.
• Comfort operating in a production environment - you handle pressure well and take ownership of reliability.
• Working knowledge of AI tools and best practices for engineering workflows.

Nice to Have

• Graph database experience (e.g., Neo4j or similar).
• ProxySQL configuration and routing experience.
• Infrastructure-as-code experience with Terraform.
• Familiarity with Prometheus and Grafana for observability and alerting.
• Prior experience in a production or trading environment.