Editorial summary

The company is Akkodis, a global engineering and R&D leader with about 50,000 engineers across 30 countries, delivering expertise across AI, data analytics, software, robotics, cybersecurity, and more. The Data Engineer role involves designing and maintaining data pipelines and analytics solutions to support digital transformation initiatives. Key requirements are not specified in the description. The compensation listed is 7500.

This summary is AI-generated and may contain inaccuracies. Please refer to the full job description below.

Job description

[This job https://singapore.job-q.com/jobs/detail/data-engineer-37593 first appeared in Job-Q.com on 13 Oct 2026]

About Akkodis

Akkodis is a global engineering and R&D leader, combining technology expertise, industry knowledge, and talent to accelerate innovation and digital transformation.

With approximately 50,000 engineers and digital experts across 30 countries spanning North America, EMEA, and APAC, Akkodis brings deep cross-sector expertise and capabilities across mobility, software and technology services, robotics, testing and simulation, cybersecurity, AI, and data analytics.

By combining engineering and IT expertise, Akkodis delivers end-to-end solutions through four service lines: Consulting, Solutions, Talents, and Academy. We help organisations rethink product development and business processes, improve productivity, accelerate time-to-market, and build a smarter and more sustainable future.

Akkodis is part of The Adecco Group and operates as the commercial brand under which AKKA and Modis entities operate.

Role Summary

Lead the design, migration, and operationof scalable data solutions on Google Cloud Platform (GCP). This role isresponsible for reliable data pipelines, governed data models, andanalytics-ready datasets that enable trusted reporting and business insights.The role partners with project managers, business stakeholders, and analyticsteams to translate requirements into secure, high-performing, andcost-effective data products.

Key Responsibilities

·      Plan and execute the migrationof enterprise data assets to GCP, including data ingestion, transformation,validation, reconciliation, and cutover support.

·      Design, build, deploy, andmaintain scalable batch and streaming ETL/ELT pipelines using services such asBigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, and Cloud Composer.

·      Develop governed,analytics-ready data models in BigQuery and implement bronze, silver, and golddata layers where appropriate.

·      Develop and govern the semanticmodel in Google Looker as the single source of truth for standardized businessmetrics, dimensions, and reporting definitions.

·      Define data integrationstrategies that meet scalability, performance, reliability, security, andcost-optimization requirements.

·      Establish automateddata-quality controls, validation rules, lineage, monitoring, alerting, andoperational support processes.

·      Apply GCP security practices,including Identity and Access Management, service accounts, least-privilegeaccess, encryption, and secure handling of sensitive data.

·      Develop reusable Python and SQLcomponents, scripts, and automation to improve data-processing efficiency andmaintainability.

·      Implement source-control,testing, deployment, and CI/CD practices for data pipelines and related cloudresources.

·      Partner with project managers,business stakeholders, and analytics teams to define key performanceindicators, metrics, data definitions, and acceptance criteria.

·      Perform data analysis androot-cause investigation to identify process improvements, data issues, andactionable business insights.

·      Create and maintain technicaldocumentation, including solution designs, data mappings, operationalprocedures, and support handover materials.

·      Experience with Power BI is anadded advantage.

Required Qualifications

·      Bachelor’s degree in ComputerScience, Data Engineering, Information Systems, Mathematics, or a relateddiscipline, or equivalent practical experience.

·      At least 3 years’ experience indata engineering, including hands-on delivery of cloud data platforms orenterprise data-migration initiatives.

·      At least 2–3 years of hands-onworking experience with Google Cloud Platform (GCP), including Google Looker.

·      Strong proficiency in SQL andPython, with experience processing and optimizing large datasets.

·      Hands-on experience withBigQuery and  GCP data services, such asDataflow, Dataproc, Cloud Storage, Pub/Sub, or Cloud Composer.

·      Demonstrated experiencedesigning, building, testing, and maintaining production-grade ETL/ELTpipelines.

·      Strong understanding of clouddata architecture, data modelling, migration patterns, reconciliation, andperformance and cost optimization.

·      Experience implementingdata-quality, governance, security, monitoring, and operational-supportcontrols.

·      Working knowledge of Git,automated testing, and CI/CD practices.

·      Strong analytical,troubleshooting, and problem-solving skills.

·      Ability to communicatetechnical concepts clearly to business and non-technical stakeholders and towork effectively across delivery teams.

Preferred Qualifications

·      Experience implementingmedallion architecture using bronze, silver, and gold data layers.

·      Experience with Apache Beam,Spark, APIs, infrastructure as code, or real-time data-processing patternswould be an added advantage.

·      Knowledge of enterprise datagovernance, metadata management, data lineage, and master-data practices.

·      Experience with Looker datamodels, dashboards, and performance optimization.

·      Relevant Google Cloudcertification, such as Professional Data Engineer.

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