Senior Data Analyst / Analytics Engineer

About the role

Coda, a global commerce platform with offices in Singapore, Amsterdam, Dubai, Bristol, Shanghai, Eindhoven and across Southeast Asia, is hiring a Senior Data Analyst / Analytics Engineer to own high-impact commercial analytics. The role sits at the intersection of business analytics, dashboarding, metric governance and analytical data modelling, supporting Commercial, Account Management, Marketing, Pay/Risk and Finance teams. It is not a reporting-only role: the person works with business leaders, goes deep into the data and returns with a clear point of view.

Key responsibilities

• Own analytics for Commercial and Account Management use cases, including publisher performance, portfolio health, margin trends, pricing impact, product performance and opportunity sizing.
• Support Commercial, Pay/Risk, Marketing and Finance teams with fast, high-quality analysis that diagnoses trends, quantifies impact and drives action.
• Translate ambiguous business questions into structured analysis, clear recommendations and decision-ready outputs.
• Build and maintain trusted analytical datasets in dbt, defining shared business logic and improving the quality of Coda's Gold layer.
• Help codify key metrics through semantic-layer tools such as LookML, the dbt semantic layer or similar governed BI patterns.
• Build dashboards in Tableau, Looker and QuickSight used by business teams to monitor performance and make decisions.
• Improve data quality and trust through dbt tests, freshness checks, anomaly detection, documentation and root-cause analysis.

Required profile

• 5+ years of experience as a Data Analyst, Analytics Engineer, BI Analyst or similar role.
• Strong business analytics experience, ideally in payments, fintech, eCommerce, gaming, digital commerce, marketplaces or high-growth internet businesses.
• Experience turning ambiguous business questions into structured analysis and recommendations.
• Strong written and verbal communication, especially with business and leadership stakeholders; able to work independently and move quickly.

Required skills

• Strong SQL and experience with large, complex datasets.
• Dashboards in Tableau, Looker, QuickSight or Power BI.
• Production experience with dbt (models, tests, documentation, reusable patterns).
• Familiarity with semantic-layer concepts such as LookML, dbt semantic layer, Cube or metrics layers.
• Working knowledge of AWS data tools such as Athena, S3, Glue, EMR or Redshift.
• Python for analytical work (pandas, numpy, basic statistics).
• Understanding of metrics such as TPV, revenue, gross profit, margin, conversion, retention, campaign performance and fraud/risk metrics.

Bonus: experience with Iceberg, Parquet or lakehouse architectures; migration from legacy BI to governed semantic layers; marketing measurement, attribution, A/B testing; payment, fraud or risk data; exposure to ML workflows or SageMaker.