Data Engineer
maneuver-marketing · India ·
- Work mode
- Remote
- Category
- Data engineering
- Experience
- 4+ years
- Company size
- 51-200
maneuver-marketing · India ·
Build and maintain data pipelines, dashboards, and analytics for a fast-growing DTC health-supplement brand, using BigQuery, dbt, and Looker to track marketing KPIs and product performance.
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!
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
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
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
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
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
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
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
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
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
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
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
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
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.