Data Intelligence Intern, trawa

• Genuine interest in data engineering, analytics engineering, or platform development
• Solid SQL skills and comfort working with data
• Basic Python programming experience
• Strong problem-solving instincts and attention to detail
• Clear communication and willingness to document your work
• Ability to work independently on scoped tasks and ask good questions when needed

Desirable

• We're looking for a Data Intelligence Intern to support the reliability, maintenance, and continuous improvement of our data platforms and operational tooling
• This is a broad, hands-on role. You'll work across real production systems - contributing to data quality, observability, platform health, and operational efficiency - while collaborating with engineers and stakeholders across the business
• Data Intelligence (DINTEL) is an engineering team that owns trawa's data pipelines, day-ahead trading automation, and analytics infrastructure.
• We manage the full data lifecycle - from ingesting raw metering and market data, through energy trading automation, to invoicing and self-service analytics
• Maintain and improve monitoring, alerting, and observability for critical data systems
• Develop data quality checks, validation processes, and operational controls
• Support backlog maintenance and cleanup across our ML and data engineering platforms
• Handle ad hoc data and platform requests from internal stakeholders
• Maintain and improve business intelligence and reporting tooling, including Metabase
• Contribute to workflow orchestration improvements - DAG sync, mapping, and scheduling
• Build operational dashboards and reports for business and ops teams
• Support Day 2 Operations: monitoring reviews, alert investigations, and Sentry improvements
• Help retire deprecated repositories, services, and technical debt
• Document processes, system changes, and operational procedures as you go
• Your First 90 Days
• First 6 weeks - Onboarding
• Get up to speed on the data platform, core pipelines, and team processes
• Contribute to routine maintenance and data quality investigations with guidance
• Start fielding data requests from other teams and business stakeholders
• By month 3 - Ramping up
• Actively own Day 2 Operations tasks: alert triage, system monitoring, stakeholder requests
• Identify and implement improvements that reduce technical debt and increase reliability
• Deliver small, well-scoped projects independently - focused on automation, observability, or data quality
• What You'll Gain;
• Hands-on experience with production data systems that power real business decisions
• Practical exposure to modern data tooling: PostgreSQL, ClickHouse, dbt, DLT, Metabase
• Skills across data engineering, analytics engineering, platform ops, and monitoring
• Direct collaboration with engineers, analysts, and business stakeholders
• Ownership of projects with clear, measurable outcomes from early on