Data Engineer (Full/Part-Time)

Build, Scale & Operate Leading DTC Brands alongside A-Players Maneuver MarketingOur Vision, Mission & Success are fuelled by our commitment to be a driving force of positive change to the health of everyday consumers, providing conscious, high-quality & innovative supplement products.In just 5 years, we kicked off our own DTC Health & Wellness brand from scratch and scaled it to USD$100M+ in annual sales, serving more than 3,000,000 customers worldwide with an average of 4,000 daily orders across 9 SKUs.These results caught the attention of The Financial Times, as they ranked us among APACs top High-Growth Companies. We have also been awarded 2nd place on the E50 Awards, jointly organised by The Business Times and KPMG in Singapore. This is just the beginning of our journey, and you could be part of the next stage of our growth!Your Next RoleWe are seeking a Data Engineer to provide ongoing operational support for our data warehouse infrastructure. This role is focused on data reliability, proactive monitoring, incident response, and continuous platform improvement, ensuring business teams can confidently rely on data for decision-making.This role is open to both full-time and part-time candidates. For part-time engagement, we are looking for a consistent commitment of 15–20 hours per week, with preferred overlap during Singapore business hours for collaboration and operational response.What You’ll doData Reliability & Pipeline MonitoringEnsure data pipelines run reliably and data is fresh, accurate, and available as expected.Monitor, build, and respond to Daton pipeline notifications and alertsTrack data latency, freshness, and completeness across all source systemsDesign, build, and maintain QC processors for all source data and custom reportsMonitor job execution, investigate failures, and perform root cause analysis at:Pipeline levelQC / validation levelAPI / source system levelCreate and enhance data pipelines, onboard new platform integrations, and implement logic changes to existing pipelinesCoordinate with source system owners and vendors when issues originate upstreamMonitor alerts from source systems and custom reportsEnsure overall data reliability through proactive monitoring and validationOptimize query performance and warehouse costsMaintain documentation for all logic, schema, and pipeline changes, with a continuously updated change logData Quality & ValidationImplement and maintain automated data quality checks (source + reports) to build trust and confidence in data across the organization.Monitor and respond to data quality and test failuresImplement automated validation checks, including; null checks, duplicate detection, range & boundary checks, valid value checks, referential integrity checksImplement business-logic validations for key KPIsPerform daily validation of critical metrics against source UIs (Shopify, GA4, Meta, Klaviyo, Google Ads, Loop, etc.)Ensure KPI consistency across raw, transformed, and reporting layersImplement anomaly detection for key tables and metricsCost OptimizationOptimize warehouse performance and manage costs proactively to ensure sustainable data operations.Monitor and respond to billing alerts for BigQuery, dbt, and ETL toolsMaintain cost monitoring dashboardsImplement and optimize table partitioning and clusteringOptimize incremental loads and expensive queriesProactively flag high-cost queries via SlackQuery performance optimization (where applicable)Source System Monitoring & (API) Integration ManagementProactively manage issues originating from upstream systems and maintain healthy integrationsMonitor and respond to source schema and data-type changesHandle source delays caused by API limits, downtime, or auth failuresCoordinate with vendors and internal teams to resolve upstream issuesAssess business impact and classify incidents as P0/P1 when requiredSecurity & ComplianceEnsure data access and handling align with regulatory requirements and security best practices.Maintain GDPR, CCPA, and related compliance controlsManage RBAC and column-level security in BigQueryEnsure PII masking and access restrictionsRespond to security incidents related to data access or credentialsDocumentation & Change ManagementMaintain documentation for pipelines, tables, and business logicUpdate test cases for logic or schema changesDocument incident RCA and resolutionsMaintain operational runbooksManage logic and schema change requests from business teamWhat You BringStrong Google BigQuery expertise (SQL optimization, partitioning, clustering)Experience with ETL tools (Daton, Fivetran, or similar)Pipeline monitoring and alerting experienceStrong SQL for debugging and validationE-commerce data experience (Shopify, GA, ad platforms preferred)Experience maintaining production data systemsStrong troubleshooting and RCA skillsClear communication with technical and non-technical stakeholdersProactive, ownership-driven mindsetAbility to work independently in a remote setupStrong documentation disciplineTime Commitment & AvailabilityFull-time5 days per week, based on our standard full-time working schedule.Part-timeExpected commitment: 15–20 hours per weekFlexible schedule, with preference for consistent weekly availabilityPreferred availability: Singapore business hours (9:00 AM – 6:00 PM SGT) for real-time collaborationResponse Time ExpectationsP0 (Critical): Acknowledgement within 2 hours on business daysP1 (High): Acknowledgement within 4 hours on business daysP2 (Standard): Acknowledgement within 24 hours

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