Job Title

Company DescriptionCodem Inc. specializes in scalable, AI-driven eCommerce solutions tailored to transform businesses across industries such as Health & Beauty, Apparel, Consumer Electronics, and Home Goods. With expertise in launching and managing over 100 global B2C and B2B eCommerce platforms, the team draws on experience from industry leaders like Amazon, HP, McKinsey, and more. Operating from offices in San Francisco, Singapore, and Chennai, Codem delivers cost-efficient solutions by utilizing specialized teams and implementing advanced AI technologies. The company helps clients streamline operations, reduce costs, and make data-driven decisions through innovative tools like Augment for AI/ML applications, custom Shopify apps, and efficient DevOps services.Role OverviewWe are looking for a highly skilled Data Engineer with strong experience in building and maintaining data pipelines for marketing and performance analytics, ideally within an e-commerce environment.The role focuses on integrating marketing and advertising data sources, building scalable pipelines, and enabling reliable reporting for campaign performance, attribution, and cost analytics.Key ResponsibilitiesData Pipeline DevelopmentDesign, build, and maintain robust data pipelines for marketing and performance datasetsDevelop and enhance API-based integrations for external data sourcesImplement Python-based ingestion and transformation workflowsData Integration & ProcessingIntegrate and process data from platforms such as:Google AdsAmazon marketing / advertising / marketplace APIsHandle multiple data sources with inconsistent schemas and API limitationsOptimize incremental data loads and transformation logicOrchestration & Workflow ManagementBuild and maintain workflows using:Apache AirflowAzure Synapse pipelines (if applicable)Ensure stable orchestration and scheduling of jobsImprove pipeline reliability and failure recovery mechanismsCloud & Data PlatformWork within Azure cloud environmentUse Spark notebooks for:Data transformationProcessing workflowsOperational data pipelinesBuild and maintain datasets in a data warehouse (DWH) environmentData Quality & ObservabilityImplement data quality checks, monitoring, and alertingTroubleshoot:Pipeline failuresAPI issuesSchema changesData discrepanciesImprove observability and scalability of data systemsBusiness CollaborationPartner with marketing and analytics teams to:Understand campaign performance requirementsSupport attribution and reporting use casesBuild datasets for:Marketing cost reportingCampaign performance analysisRequired SkillsCore Engineering SkillsStrong experience as a Data EngineerAdvanced Python for:API integrationsData processingPipeline developmentStrong SQL skillsData Engineering & ArchitectureSolid understanding of:Data warehousing conceptsData modellingETL / ELT designTools & TechnologiesApache AirflowAzure CloudSpark / Spark NotebooksExperience with API-based data ingestionMarketing Data ExperienceHands-on experience with:Google Ads APIsAmazon marketing / marketplace dataExperience building datasets for:Campaign performanceMarketing cost reportingData OperationsExperience with:Data quality validationMonitoring & alertingTroubleshooting production pipelinesPreferred / Ideal ExperienceExperience in:Performance marketing or attribution data engineeringHandling multi-source data pipelines with schema inconsistenciesOptimizing:Incremental loadsCost-efficient data processingPipeline orchestration reliabilityDirect collaboration with marketing / analytics stakeholdersNice to HaveExperience with retail media / marketplace data ecosystemsAdvanced experience with SparkUnderstanding of:Marketing attribution modelsMulti-touch attribution logicCandidate ProfileThe ideal candidate is:Hands-on and technically strongProactive in identifying and resolving issuesFocused on pipeline reliability and scalabilityBusiness-aware with understanding of marketing metricsStructured and pragmatic in a production environment