{"id":121524,"url":"https://alion.io/job/coda-senior-data-analyst","title":"Senior Data Analyst","company":{"id":51279,"name":"Coda","domain":"coda.co","url":"https://alion.io/company/coda-co","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"Analytics","role_family":"Analytics","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":54000,"max_usd":101000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":39},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"AWS","optional":false},{"name":"dbt","optional":false},{"name":"Looker","optional":false},{"name":"LookML","optional":false},{"name":"NumPy","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"A/B Testing","optional":true},{"name":"Amazon SageMaker","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-08-14T02:00:19Z","employer_posted_date":"2026-08-14","last_verified_at":"2026-10-18T05:39:15Z","board_verified":true,"closed_at":null,"days_open":65,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":65},"description":"Data Science & Analytics at Coda\nAt Coda, the Data Science & Analytics team turns data into business decisions.\nWe work closely with Commercial, Account Management, Marketing, Pay/Risk, Finance, and Product teams. Our work directly influences revenue growth, margin performance, risk management, campaign effectiveness, and operational efficiency.\nOur stack runs on AWS, with dbt for transformation, Athena and Spark over an Iceberg and Parquet data lake, Python for analysis, and BI tools including QuickSight, Tableau, and Looker. We are also building a stronger analytics foundation: moving from fragmented legacy reporting to trusted Gold datasets, clearer metric ownership, and stronger semantic-layer practices.\nThe Opportunity\nWe are hiring a Senior Data Analyst / Analytics Engineer to own high-impact commercial analytics across Coda.\nThis role sits at the intersection of business analytics, dashboarding, metric governance, and analytical data modeling. You will support Commercial, Account Management, Marketing, Pay/Risk, and Finance by turning raw data into trusted metrics, decision-ready dashboards, and clear business recommendations.\nThis is not a reporting-only role. We are looking for someone who can sit with business leaders, understand the decision that needs to be made, go deep into the data, and come back with a clear point of view.\nThe ideal candidate is commercially sharp, technically strong, comfortable with ambiguity, and able to move quickly without compromising analytical quality.\nWhat you'll do\nOwn analytics for Commercial and Account Management use cases, including publisher performance, portfolio health, margin trends, pricing impact, product performance, and opportunity sizing.\n\nSupport Commercial, Pay/Risk, Marketing, and Finance teams with fast, high-quality analysis that helps diagnose trends, quantify impact, and drive business action.\n\nTranslate ambiguous business questions into structured analysis, clear recommendations, and decision-ready outputs.\n\nBuild and maintain trusted analytical datasets in dbt, helping define shared business logic and improve the quality of Coda’s Gold layer.\n\nHelp codify key metrics through semantic-layer tools such as LookML, the dbt semantic layer, or similar governed BI patterns.\n\nBuild dashboards in Tableau, Looker, and QuickSight that business teams actually use to monitor performance, identify issues, and make decisions.\n\nImprove data quality and trust through dbt tests, freshness checks, anomaly detection, documentation, and root-cause analysis.\n\nWhat you'll bring\n5+ years of experience as a Data Analyst, Analytics Engineer, BI Analyst, or similar role.\n\nStrong SQL skills and experience working with large, complex datasets.\n\nStrong business analytics experience, ideally in payments, fintech, eCommerce, gaming, digital commerce, marketplaces, or high-growth internet businesses.\n\nExperience translating ambiguous business questions into structured analysis and clear recommendations.\n\nExperience building dashboards in Tableau, Looker, QuickSight, Power BI, or similar tools.\n\nProduction experience with dbt, including models, tests, documentation, and reusable transformation patterns.\n\nFamiliarity with semantic-layer concepts such as LookML, dbt semantic layer, Cube, metrics layers, or governed BI models.\n\nWorking knowledge of AWS data tools such as Athena, S3, Glue, EMR, Redshift, or similar cloud data platforms.\n\nPython skills for analytical work, especially pandas, numpy, and basic statistical analysis.\n\nStrong understanding of business metrics such as TPV, revenue, gross profit, margin, conversion, retention, campaign performance, fraud/risk metrics, and account performance.\n\nStrong written and verbal communication skills, especially with business and leadership stakeholders.\n\nAbility to work independently, prioritize well, and move quickly in a fast-changing business environment.\n\nBonus if you have\nExperience with Iceberg, Parquet, or modern lakehouse architectures.\n\nExperience migrating from legacy BI/reporting environments to governed semantic layers.\n\nExperience with marketing measurement, attribution, incrementality, A/B testing, geo tests, or matched-market tests.\n\nExperience working with payment, fraud, risk, or transaction data.\n\nExperience supporting Commercial, Account Management, Finance, or executive stakeholders.\n\nExposure to ML workflows, SageMaker, or AI-assisted analytics workflows.","description_format":"text","description_chars":4433,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Singapore","iso":"SG","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Payment Processing & Gateways","Digital 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