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! Role Overview We are looking for a highly analytical and business-oriented Data Analyst to own reporting, performance analysis, and decision-support across our business. This role will serve as a key partner to Growth, Marketing, Product, and Leadership teams by transforming data into actionable insights that drive revenue, profitability, and operational efficiency. The ideal candidate combines strong technical skills (SQL is mandatory) with commercial acumen, enabling them to identify opportunities, evaluate business performance, and support strategic decision-making. Experience with automation, AI-powered analytics, performance marketing, and eCommerce environments is highly desirable. Key Responsibilities Reporting & Dashboard Ownership • Own and maintain the company-wide reporting infrastructure, including dashboards, KPI trackers, and automated reports • Build, improve, and manage recurring reports for Growth, Marketing, Product, Finance, and Operations teams • Design and develop executive-level dashboards that support leadership decision-making • Manage and iterate on existing dashboards, updating metrics, adding dimensions, and evolving reporting as the business changes • Own data quality and governance, metric definitions, documentation, and reporting standards • Ensure accuracy, consistency, and reliability of all business metrics and data outputs Data Pipeline & Automation • Partner with engineering and operational teams to improve data collection, tracking, and pipeline reliability • Leverage AI tools and advanced analytics techniques to improve reporting efficiency and insight generation • Independently build and maintain data pipelines using dbt or equivalent to support clean, reliable analytical layers Growth & Marketing Analytics • Partner closely with the Growth team to analyze performance across paid media channels • Evaluate campaign performance, customer acquisition trends, CAC, ROAS, MER, LTV, retention, and other growth metrics • Conduct deep-dive analyses to identify growth opportunities and performance drivers • Analyze promotional performance and measure the impact of marketing initiatives Product & Commercial Analysis • Monitor and evaluate product performance across SKUs, channels, and markets • Analyze purchasing patterns, customer segmentation, pricing impact, and promotional effectiveness • Identify opportunities to improve product assortment, pricing decisions, and inventory allocation • Provide recommendations based on quantitative analysis and business impact Ad-Hoc Analysis & Decision Support • Respond to analytical requests from cross-functional teams with structured, business-ready outputs • Investigate business challenges, identify root causes, and present actionable recommendations • Support experimentation and A/B testing efforts — helping design tests, interpreting results, and communicating outcomes to stakeholders • Translate complex datasets and quantitative findings into clear narratives for non-technical stakeholders Analytical Operations • Coordinate and manage VAs on data-related tasks — scoping work, reviewing outputs, maintaining quality • Flag data integrity issues proactively and drive resolution across relevant teams • Support experimentation and hypothesis testing as the role and business matures Required Qualifications Technical • Advanced SQL — window functions, CTEs, complex joins, query optimisation • Proficient in at least one BI tool — Tableau, Power BI, Looker, Metabase, or similar • Experience with a cloud data warehouse — BigQuery, Snowflake, Redshift, or Databricks • Experience with data transformation tools and ETL concepts — dbt, Databricks, or equivalent • Strong Excel or 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 • Awareness of analytical models — subscription LTV, cohort analysis, funnel metrics • Familiarity with A/B testing methodology — experiment design and hypothesis testing Communication, Collaboration & Adaptability • Communicates findings clearly to both technical and non-technical audiences • Adapts output and framing for different stakeholders — executives, growth, product, operations • Collaborative across functions; coordinates effectively with VAs and cross-functional teams • Comfortable with ambiguity, shifting priorities, and self-directed learning Experience • 3 to 5 years in Data Analytics, Business Intelligence, or a related field • Proven experience independently building dashboards, automated reporting and strategic analysis Preferred Qualifications The following are strong-to-have — candidates without all of these are still encouraged to apply. • Experience in eCommerce, DTC, subscription, or consumer goods • Proficiency in Python or R for data manipulation or workflow automation • Familiarity with marketing KPIs — CAC, ROAS, MER, LTV:CAC, contribution margin • Familiarity with marketing concepts: customer journey mapping, funnel analysis, cohort retention, incrementality testing • Experience with A/B testing or experimentation frameworks • Experience with ETL processes, API data extraction, or data pipeline tooling • Familiarity with additional databases — PostgreSQL, MySQL, MongoDB, or Azure SQL • Experience implementing AI-powered analytics workflows or reporting automation Success in the First 12 Months • Own and automate reporting across key business functions, reducing manual effort and improving data reliability • Independently build and maintain data pipelines in collaboration with engineering and operations, reducing dependency on manual data pulls • Drive analytical ownership for the Growth team — from campaign performance to retention and product analytics • Deliver insights that directly influence marketing efficiency, budget allocation, and promotional decisions • Improve visibility into product and promotional performance across SKUs and channels • Coordinate VAs effectively on data tasks, ensuring quality and consistency of outputs • Develop sufficient working knowledge of DTC marketing and subscription concepts to provide commercially grounded analysis • Enable leadership to make faster, better-informed decisions through accessible, trustworthy data