Databento
Systems Engineer
Remote / Boston / Salt Lake City / San Francisco / New York · Intern · Internship
No sponsorshipDetected 13 days ago
PythonMySQLRedisAWSGCPDockerKubernetesTerraformAnsibleLinuxPrometheusGrafanaDevOpsRecruitingCustomer SupportSystems EngineeringResearchProblem Solving
About the role
- The company provides real-time and historical data across futures, options, and equities through a unified API.
- We accommodate 100% remote work, with teammates living around the globe and paid in their local currency.
- Notice about phishing scams Be cautious of phishing scams impersonating Databento that offer fake job interviews and request purchases.
Responsibilities
- On-call support.
- Customer support experience and strong problem-solving abilities.
- Our team includes alumni of Two Sigma, Citadel Securities, Flow Traders, Tower Research, PDT Partners, SIG, and other top quantitative firms.
Requirements
- Ability to code in Python and write shell scripts.
- Prior internship experience or 2+ years in full-time systems engineering or infrastructure roles.
- Bachelor's degree in Computer Science or a related field.
- Candidates must be authorized to work in the U.S.
- Experience with distributed storage systems (e.g., Ceph).
Nice to have
- Experience with systems configuration and provisioning (PXE, Puppet, and Ansible preferred
Compensation
- This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
Benefits
- We offer health, dental, disability, and life insurance benefits, as well as 401(k) matching for full-time employees.
- Prior experience at a trading or fintech firm, or a strong interest in learning fintech.
Company info
- Coordinating bulk data delivery to customers and vendor partners.
Visa & Work Authorization
- Candidates must be authorized to work in the U.S.; H-1B visa sponsorship is not available.
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This listing is sourced directly from Databento's careers page and normalized into a canonical job model.