Data Engineer / Analytics Engineer (Intern)
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.
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.