Data Engineer & Analyst

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!

What You'll Own

1. Data Infrastructure & Pipeline Reliability

Keep data flowing accurately, on time, and at cost.

• Monitor, build, and respond to Daton pipeline alerts; track latency, freshness, and completeness across all source systems

• Investigate pipeline failures and perform root cause analysis at the pipeline, QC/validation, and API/source system level

• Create and enhance data pipelines; onboard new platform integrations and implement logic changes to existing ones

• Coordinate with source system owners and vendors when issues originate upstream

• Optimize query performance and warehouse costs; implement table partitioning, clustering, and incremental load strategies

• Maintain documentation for all pipeline logic, schema changes, and incidents, with a continuously updated change log

2. Data Quality & Validation

Build and maintain the quality layer that makes data trustworthy across the organization.

• Design and maintain automated QC checks: null checks, duplicate detection, range/boundary checks, valid value checks, referential integrity, and 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

• Proactively flag and resolve data integrity issues across teams

3. Reporting & Dashboard Ownership

Own the company-wide reporting infrastructure.

• Build, maintain, and evolve dashboards and KPI trackers for Growth, Marketing, Product, Finance, and Operations

• Design and manage executive-level dashboards that support leadership decision-making

• Own metric definitions, documentation, and reporting standards across the organization

• Leverage dbt (or equivalent) to maintain clean, reliable analytical layers

• Use AI tools and automation to improve reporting efficiency and reduce manual effort

4. Growth & Marketing Analytics

Be the analytical partner the Growth team relies on.

• Analyze performance across paid media channels - CAC, ROAS, MER, LTV, retention, and contribution margin

• Conduct deep-dive analyses to identify growth opportunities and performance drivers

• Evaluate promotional performance and measure the impact of marketing initiatives

• Support experimentation and A/B testing: help design tests, interpret results, and communicate outcomes to stakeholders

5. Product & Commercial Analysis

Turn data into commercial decisions.

• Monitor and evaluate product performance across SKUs, channels, and markets

• Analyze purchasing patterns, customer segmentation, pricing impact, and promotional effectiveness

• Provide recommendations based on quantitative analysis and business impact

• Identify opportunities to improve product assortment, pricing decisions, and inventory allocation

6. Ad-Hoc Analysis & Decision Support

Respond fast and think clearly under ambiguity.

• Answer analytical requests from cross-functional teams with structured, business-ready outputs

• Investigate business challenges, identify root causes, and present actionable recommendations

• Translate complex datasets and quantitative findings into clear narratives for non-technical stakeholders

• Coordinate and manage VAs on data-related tasks - scoping work, reviewing outputs, maintaining quality

7. Security, Compliance & Access Management

Protect data and maintain regulatory alignment.

• 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

Technology Stack

• Data Warehouse: Google BigQuery

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

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

• Source Systems: Shopify, GA4, Meta Ads, Google Ads, Klaviyo, Loop Subscriptions, Recart, Postscript, PayPal, and 20+ additional sources

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

Required Qualifications

Technical

• Strong Google BigQuery expertise - SQL optimization, partitioning, clustering

• Advanced SQL - window functions, CTEs, complex joins, query optimization

• Experience with ETL tools (Daton, Fivetran, or similar) and pipeline monitoring

• Experience with dbt or equivalent data transformation tools

• Proficiency in at least one BI tool - Looker, Tableau, Power BI, Metabase, or similar

• E-commerce data experience (Shopify, GA4, ad platforms strongly preferred)

• Strong Excel / Google Sheets for ad-hoc analysis

• Experience using AI tools for automation, workflow improvement, or analytics

Analytical

• Structured problem-solving - breaks ambiguous business questions into clear analytical frameworks

• Independently identifies trends, risks, and opportunities without a specific brief

• Familiarity with subscription LTV, cohort analysis, funnel metrics, and A/B testing methodology

Professional

• 4-6 years of experience spanning data engineering and analytics (or a strong hybrid track record)

• Proven experience maintaining production data systems with strong troubleshooting and RCA skills

• Clear communication with both technical and non-technical stakeholders

• Proactive, ownership-driven mindset; ability to work independently in a remote setup

• Strong documentation discipline

• Response availability: P0 within 2 hours, P1 within 4 hours, P2 within 24 hours on Singapore business days

Preferred Qualifications

• Experience in eCommerce, DTC, subscription, or consumer goods

• Proficiency in Python for data manipulation or workflow automation

• Familiarity with marketing KPIs - CAC, ROAS, MER, LTV:CAC, contribution margin

• Experience with A/B testing or experimentation frameworks

• Familiarity with additional databases - PostgreSQL, MySQL, MongoDB, or Azure SQL

• Experience implementing AI-powered analytics workflows or reporting automation

What Success Looks Like in Year One

• Data pipelines are monitored proactively, incidents are resolved fast, and business teams trust the data they rely on

• Reporting across key business functions is automated and accurate, with reduced manual effort and clear metric ownership

• The Growth team has a strong analytical partner - from campaign performance to retention to product analytics

• Insights directly influence marketing efficiency, budget allocation, and promotional decisions

• Product and promotional performance is visible across SKUs and channels, with clear recommendations for action

• Leadership makes faster, better-informed decisions through accessible, trustworthy data

Maneuver Marketing is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.