Build, Scale & Operate Leading DTC Brands alongside A-Players

Maneuver Marketing

Our 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 Role

We 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 do

Data Reliability & Pipeline Monitoring

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

Data Quality & Validation

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

Cost Optimization

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)

Source System Monitoring & (API) Integration Management

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

Security & Compliance

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

Documentation & Change Management

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

What You Bring

• 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

Time Commitment & Availability

Full-time
5 days per week, based on our standard full-time working schedule.

Part-time

Expected commitment: 15–20 hours per week

Flexible schedule, with preference for consistent weekly availability

Preferred availability: Singapore business hours (9:00 AM – 6:00 PM SGT) for real-time collaboration

Response Time Expectations

P0 (Critical): Acknowledgement within 2 hours on business days

P1 (High): Acknowledgement within 4 hours on business days

P2 (Standard): Acknowledgement within 24 hours