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Work Model: Remote (APAC-aligned hours / Singapore time preferred)
Engagement: Fractional (part-time 15–30 hrs/week) with a defined path to Full-Time employment (6–9 months), or Full-Time hire if candidate prefers
Reporting Into: Business & Analytics Leadership
Start Date: Immediate
About the Opportunity
A fast-growing e-commerce business is scaling its data infrastructure and seeking a hands-on Data Engineer / Data Operations Engineer who can own and operate their production data warehouse environment end-to-end.
This role is not a traditional analytics support position — the focus is on ensuring pipeline reliability, automated QC, operational reporting, real-time monitoring, and stability of mission-critical business data flows. The right candidate will have both strong technical depth AND the ability to work independently, running and troubleshooting complex data pipelines with minimal supervision.
The ideal hire will start in a fractional capacity, proving impact quickly, and convert to a full-time engineering role once there is mutual alignment and clear demand growth.
Why This Role Matters
This position is central to daily business execution. The data platform supports 30+ integrations, including core e-commerce and ad platforms. Reports are published daily across the entire organization, so this hire must ensure the end-to-end reliability of systems that influence revenue decisions and operational planning.
Key Responsibilities
The successful candidate will:
Data Pipeline Operations & Reliability
Monitor, maintain and proactively troubleshoot data pipelines feeding the warehouse (primarily BigQuery + ETL tools).
Identify, diagnose, and resolve pipeline failures, latency issues, and data quality problems.
Perform root cause analysis (RCA) for failures — including API source issues, pipeline breakages, logic errors, or schema drift — and document fixes and preventative measures.
Maintain automated alerting and job-validation mechanisms (e.g., Slack alerts, email notifications) for critical pipeline health.
Data Quality, Validation & Reporting
Implement and maintain validation checks (nulls, duplicates, referential integrity, logic checks) that reduce manual QC work.
Build and refine business-logic validations into reporting workflows to enforce accuracy.
Support daily report validation and publication, including escalation and corrections during promotional events (Prime Day, BFCM, seasonal spikes).
Custom Integrations & Transformations
Develop additional data pipelines and transformation logic as new business needs arise.
Work with dbt and custom scripts to maintain and grow transformation layers.
Governance, Documentation & Process
Build and maintain documentation for pipelines, schemas, and operations runbooks.
Define and enforce access controls, security best practices, and QA standards.
Track and report on reliability metrics and pipeline uptime consistently.
Incident Response & SLA Support
Provide P0 incident support (immediate, live triage), with timely resolution during business hours.
Support P1 logic updates and custom metrics builds in partnership with business stakeholders.
Conduct P2 documentation and handover on completed integrations and pipeline changes.
Cross-Functional Collaboration
Work directly with analytics, business operations, and reporting stakeholders to understand needs and translate them into robust data operations.
Act as the technical lead on the data side, and support knowledge sharing where necessary.
Required Skills & Experience
The ideal candidate will demonstrate:
Technical Capability
Strong SQL proficiency, especially in BigQuery (optimization, partitioning, clustering, debugging).
Proven experience owning production ETL pipelines (Daton, Fivetran, Stitch, or similar).
Experience building data quality frameworks and validation checks.
Exposure to dbt, data transformations, and incremental loads.
Domain Expertise
Prior work in e-commerce data environments (Shopify, Meta Ads, Google Ads, subscriptions platforms).
Demonstrated aptitude managing complex integrations and evolving business contexts.
Operational Discipline
Comfortable working independently and managing their own output.
Strong troubleshooting mindset and ability to produce clear RCA documentation.
Clear communicator across technical and non-technical teams.
Professional Profile
Minimum 3+ years of relevant data engineering or operations experience in a production environment.
Experience maintaining mission-critical data systems that support daily business decisions.
Strong documentation discipline and proactive ownership ethic.
Work Schedule & Expectations
Core hours aligned to Singapore time zone (critical for responsive incident handling and validation flows).
Part-time engagements may still require availability Saturday for critical report review and QC during peak periods — coordinated with business leadership.
Slack is primary communication channel; outside core hours priority responses via email are acceptable with proper SLA definitions.
Compensation & Growth Path
Initial compensation will align with experience and engagement model. For fractional hires, this ranges within the client’s budget of approximately $2,000–$4,000 SGD/month, with expectations set on experience level and market competitiveness.
Full-time conversion is expected within 6–9 months given performance and business alignment.
Candidates based in India, Vietnam, Philippines or other APAC regions will be considered to align with the client’s global compensation expectations.
Ideal Candidate Summary
This role is designed for a self-sufficient engineer who:
Thrives running production data environments
Understands the nuances of e-commerce platforms
Can independently resolve pipeline failures and build automated QC tooling
Is comfortable operating in a remote, collaboration-dependent context
Sees fractional engagement as a pathway to broader ownership and influence
To apply for this job email your details to kinnari@axerecruiting.com