Data Engineer

Maneuver Marketing; Remote; SGD 60,000 - 80,000; Part time

Job summary

A dynamic marketing firm in Singapore is seeking a part-time Data Engineer to support their data warehouse infrastructure. This role emphasizes data reliability, proactive monitoring, and incident response, ensuring teams can depend on data for decision-making. The ideal candidate has strong expertise in Google BigQuery and experience with ETL tools. With a flexible commitment of 15-20 hours per week, this position allows for real-time collaboration during Singapore business hours and is perfect for candidates looking to contribute to a growing company.

Benefits

Flexible schedule

Work from home

Collaboration with A-Players

Qualifications

• Experience maintaining production data systems.
• Strong troubleshooting skills and root cause analysis.
• Clear communication with both technical and non-technical teams.

Responsibilities

• Ensure data pipelines run reliably and data is available as expected.
• Implement and maintain automated data quality checks.
• Optimize warehouse performance and manage costs proactively.

Skills

Google BigQuery expertise

ETL tools experience

Pipeline monitoring experience

Strong SQL for debugging

E-commerce data experience

Job description

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!

The Role

We are seeking a part-time 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.

Time Commitment & Availability

• Expected commitment: 15–20 hours per week (flexible schedule)

• 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

Technology Stack

• Data Warehouse: Google BigQuery

• ETL / Data Movement: Daton (primary), custom pipelines, dbt

• BI / Activation: Looker, Qlik, Segment (in progress)

• Source Systems: 30+ platforms including Shopify, GA4, Meta Ads, Google Ads, Klaviyo, Loop Subscriptions, Recart, Postscript, PayPal, and others

• Monitoring & Alerting: Slack alerts, custom monitoring framework, email notifications

Core Responsibilities

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.

Key Activities:

• Monitor and respond to data quality and test failures

• Implement automated validation checks, including:

  • Null checks

  • Duplicate detection

  • Range and 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.

Key Activities:

• 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.

Key Activities:

• 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.

Key Activities:

• 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

Ensure operational continuity and knowledge transfer

Key Activities:

• 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 teams

Required Technical Skills

• 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)

Required Professional Skills

• 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

Nice to Have

• 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