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.

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

1. 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

1. 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

1. 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

1. 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

1. 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

1. 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.