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