Senior Analytics Engineer

Maya; Mandaluyong; On-site; PHP 1,200,000 - 2,000,000; Full time

Job summary

Maya is building an all-in-one money platform in the Philippines. We are seeking an Analytics Engineer to design, develop, and maintain scalable data products, feature stores, and transformation frameworks for data scientists to build and deploy machine learning solutions.

The ideal candidate has strong experience in dbt, SQL, data modeling, Databricks, cloud platforms, and feature engineering pipelines. You will bridge Data Engineering and Data Science to ensure high-quality, trusted data for

Qualifications

• Bachelor's degree in a quantitative field is required.
• 4+ years of experience in Analytics Engineering or Data Engineering.
• 2+ years of hands-on dbt in production environments.
• Strong expertise in SQL, data modeling, and ETL/ELT development.

Responsibilities

• Design, develop, and maintain scalable data models and transformation pipelines.
• Build and manage feature stores and pipelines for model training and inference.
• Collaborate with Data Scientists and ML Engineers for production readiness.
• Ensure data quality, lineage, governance, and documentation across assets.

Skills

Analytical thinking

Collaboration

Communication

Problem solving

Education

Bachelor's degree in Computer Science, Information Technology, Statistics, Engineering, Mathematics, or related quantitative discipline

Tools

dbt (DataBuildTool)

Databricks

Apache Spark

Cloud platforms (AWS/Azure/GCP)

CI/CD pipelines

Job description

Our goal is for everyone to make bolder choices with their finances.

To get there, we're creating an all-in-one ecosystem of financial services for today's generation of goal-getters. That feat takes extraordinary people-those with the guts to challenge the way things are and transform them into something better.

To be part of Team Maya is to be Bolder for Better.

Description: AsanAnalyticsEngineer,youwillberesponsiblefordesigning,developing,andmaintainingscalabledataproducts,featurestores,datamodels,andtransformationframeworksthatenableDataScientiststoefficientlybuild,deploy,andoperationalizemachinelearningsolutions.

YouwillserveasthebridgebetweenDataEngineeringandDataScience,ensuringthathigh-quality,trusted,andwell-modeleddataisreadilyavailableforanalytics,experimentation,andmachinelearningusecases.Theidealcandidatehasstrongexperienceindbt,SQL,datamodeling,Databricks,cloudplatforms,andfeatureengineeringpipelines.

WHATYOUWILLDO:

DataModeling&Transformation

• PartnercloselywithDataScientiststodesign,develop,andmaintaindatasetsthatsupportstatisticalanalysis,machinelearningmodels,experimentation,andbusinessinsights.
• Design,build,andoptimizescalabledatamodelsusingdbt(DataBuildTool)followingindustrybestpracticesformodularity,testing,documentation,andmaintainability.
• Developandmanagetransformationpipelinesthatconvertrawdataintotrusted,analytics-readydatasets.
• Establishandmaintaindatalineage,governance,anddocumentationacrossanalyticaldataassets.

FeatureStore&MLDataPlatform

• Design,develop,andmaintainfeaturestoresandaccompanyingfeaturepipelinesusedformodeltraining,featureserving,andbatchinference.
• Implementreusablefeatureengineeringframeworksthatacceleratemachinelearningdevelopmentandimprovefeatureconsistency.
• CollaboratewithDataScientistsandMachineLearningEngineerstoensurefeaturereusabilityandproductionreadiness.
• Supportthedesignandmaintenanceofreal-timeandbatchfeaturepipelines.

DataQuality,Governance&Reliability

• Implementautomateddatavalidation,monitoring,andtestingframeworkstoensuredataqualityandreliability.
• Establishdataqualitychecks,SLAs,observabilitymetrics,andmonitoringprocessesacrosscriticaldatasetsandpipelines.
• PartnercloselywithDataEngineeringandDataGovernanceteamstoimprovedatamaturity,accessibility,andtrustworthiness.
• Serveasasubjectmatterexpertacrossassignedbusinessanddatadomains.

PlatformEngineering&BestPractices

• BuildCI/CDpipelinesthatacceleratedeploymentandproactivelydetectissuesbeforeproductionrelease.
• Createandmaintainreusablesoftwarepackages,tools,andframeworksthatimproveDataScienceproductivity.
• Establishbestpracticesfordatamodeling,transformation,testing,deployment,andarchitecture.
• Conductcodereviewsandarchitecturalreviewstoensureadherencetoengineeringstandards.
• Communicatetechnicalarchitectures,trade-offs,andsolutionstobothtechnicalandnon-technicalstakeholders.
• Maintainarchitecturediagrams,technicaldocumentation,andplatformstandards.

WHATWE'RELOOKINGFOR:

• Bachelor'sdegreeinComputerScience,InformationTechnology,Statistics,Engineering,Mathematics,orarelatedquantitativediscipline.
• Atleast4+yearsofexperienceinAnalyticsEngineering,DataEngineering,orrelatedfields.
• Atleast2+yearsofhands-onexperiencewithdbt(DataBuildTool)inaproductionenvironment.
• StrongexpertiseinSQL,datamodeling,andETL/ELTdevelopment.
• ExperiencewithDatabricks,ApacheSpark,ormodernLakehouseplatforms.
• ExperienceworkingwithcloudtechnologiessuchasAWS,Azure,orGCP.
• ExperiencebuildingandmaintainingCI/CDpipelinesandautomatedtestingframeworks.
• ExperiencecollaboratingwithDataScience,DataEngineering,andbusinessstakeholders.
• Experienceworkingwithlarge-scaledatasetsandcomplexdataecosystems.

About Us

Maya is the all-in-one money platform that is bringing Filipinos bolderways to master their money.It is powered by a unique integrated financial services ecosystem that addresses the ever-evolving needs of today’s generation of moneymakers through cutting edge technology.

Welead millions of Filipinos — consumers, businesses,communities, and government agencies alike — into a version ofthe current digital economy that’s more inclusive, transparent,and empowering than ever.

We arepowered by the country's only end-to-end digital payments company Maya Philippines, Inc. and Maya Bank, Inc. for digital banking services.

Maya Bank, Inc. and Maya Philippines, Inc. are regulated by the Bangko Sentral ng Pilipinas. https://www.bsp.gov.ph/