Key skills
BigQueryETLSQLdbtFivetranShopifyPerformance OptimizationCommunicationCollaboration
About this role
Role Overview
- Ensure data pipelines run reliably and data is fresh, accurate, and available as expected.
- Monitor, build, and respond to Daton pipeline notifications and alerts
- Track data latency, freshness, and completeness across all source systems
- Design, build, and maintain QC processors for all source data and custom reports
- Monitor job execution, investigate failures, and perform root cause analysis at:
- Pipeline level
- QC / validation level
- API / source system level
- Create and enhance data pipelines, onboard new platform integrations, and implement logic changes to existing pipelines
- Coordinate with source system owners and vendors when issues originate upstream
- Monitor alerts from source systems and custom reports
- Ensure overall data reliability through proactive monitoring and validation
- Optimize query performance and warehouse costs
- Maintain documentation for all logic, schema, and pipeline changes, with a continuously updated change log
- Implement 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 failures
- Implement automated validation checks, including; null checks, duplicate detection, range & boundary checks, valid value checks, referential integrity checks
- Implement business-logic validations for key KPIs
- Perform daily validation of critical metrics against source UIs (Shopify, GA4, Meta, Klaviyo, Google Ads, Loop, etc.)
- Ensure KPI consistency across raw, transformed, and reporting layers
- Implement anomaly detection for key tables and metrics
- Optimize warehouse performance and manage costs proactively to ensure sustainable data operations.
- Monitor and respond to billing alerts for BigQuery, dbt, and ETL tools
- Maintain cost monitoring dashboards
- Implement and optimize table partitioning and clustering
- Optimize incremental loads and expensive queries
- Proactively flag high-cost queries via Slack
- Query performance optimization (where applicable)
- Proactively manage issues originating from upstream systems and maintain healthy integrations
- Monitor and respond to source schema and data-type changes
- Handle source delays caused by API limits, downtime, or auth failures
- Coordinate with vendors and internal teams to resolve upstream issues
- Assess business impact and classify incidents as P0/P1 when required
- Ensure data access and handling align with regulatory requirements and security best practices.
- Maintain GDPR, CCPA, and related compliance controls
- Manage RBAC and column-level security in BigQuery
- Ensure PII masking and access restrictions
- Respond to security incidents related to data access or credentials
- Maintain documentation for pipelines, tables, and business logic
- Update test cases for logic or schema changes
- Document incident RCA and resolutions
- Maintain operational runbooks
- Manage logic and schema change requests from business team
Requirements
- Strong Google BigQuery expertise (SQL optimization, partitioning, clustering)
- Experience with ETL tools (Daton, Fivetran, or similar)
- Pipeline monitoring and alerting experience
- Strong SQL for debugging and validation
- E-commerce data experience (Shopify, GA, ad platforms preferred)
- Experience maintaining production data systems
- Strong troubleshooting and RCA skills
- Clear communication with technical and non-technical stakeholders
- Proactive, ownership-driven mindset
- Ability to work independently in a remote setup
- Strong documentation discipline
Tech Stack
- BigQuery
- ETL
- SQL
Benefits
- Flexible schedule, with preference for consistent weekly availability
- Preferred availability: Singapore business hours (9:00 AM – 6:00 PM SGT) for real-time collaboration