About the Role

We’re looking for a Data Engineering / Analytics Intern who wants to build reliable data systems—not just dashboards.

You’ll work on designing and maintaining data pipelines for logs, usage, quality metrics, and customer analytics in a fast-moving environment where schemas and questions evolve constantly. This means ensuring data is accurate, trustworthy, and useful for decision-making across product and business teams.

You’ll collaborate closely with founders, product, and engineering to turn raw data into actionable insights. Your work will directly impact experimentation, reporting, and how the company makes decisions.

If you enjoy working with messy data, building systems end-to-end, and improving data quality, this role will push you to grow quickly.

What You Will Do

• Design and implement ETL/ELT pipelines for logs, usage, and analytics

• Build and maintain transformation layers (dbt or similar)

• Set up data quality checks and monitoring for key datasets

• Model data in warehouses or lakes for analytics use cases

• Support experimentation, reporting, and feedback loops with reliable data

• Ensure privacy-aware handling of sensitive data (PII)

• Document data models, metrics, and pipelines clearly

What We’re Looking For

• Strong SQL fundamentals

• Familiarity with ETL/ELT workflows and tools

• Exposure to dbt or similar transformation frameworks

• Experience with a data warehouse or data lake

• Basic understanding of batch vs real-time data processing

• Awareness of data privacy and compliance considerations

Founding Mindset

• You think in terms of user-perceived reliability, not just dashboards

• You ask “what does good reliability look like?” before adding metrics

• You take ownership of uptime and graceful degradation

• You balance speed of change with system stability

• You proactively identify reliability gaps before they cause incidents

Bonus

• Experience with observability tools like Prometheus, Grafana, or OpenTelemetry

• Exposure to incident management or on-call workflows

• Experience with resilience testing or chaos engineering

• Familiarity with tracing and structured logging

What Success Looks Like

Within 4–6 weeks, you should be able to:

• Own monitoring and alerting for a subset of services

• Reduce noisy alerts and improve signal quality

• Contribute to incident retrospectives with actionable insights

• Improve reliability, visibility, or response time in a measurable way

What You’ll Get

• Hands-on experience building reliability practices from the ground up

• Direct collaboration with founders and core engineering teams

• Real ownership beyond a typical SRE internship

• A portfolio of dashboards, runbooks, and system improvements

• A strong pathway into SRE, platform, or production engineering roles

Who This Is Not For

• If you want predictable systems with no incidents to handle

• If you avoid ambiguity or cross-team problem solving

• If you prefer rigid, siloed environments with predefined processes

Who Will Thrive Here

• Builders who want to actively own system reliability

• Engineers who think in terms of end-to-end systems

• Calm debuggers of intermittent and complex failures

• High-agency individuals who care about keeping systems running reliably

About the Company

We’re building the speech intelligence layer for Southeast Asia—turning real-world, accented, code-switched speech into structured, usable outputs for businesses.