Senior Software Engineer, Data Backend EDP (Enterprise Data Platform) - Tokyo,Japan

Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. Our EDP team builds core data backend capabilities that power critical product experiences across ingestion, profile processing, and serving.

We are hiring a Senior Software Engineer, Data Backend to design and operate production-grade data backend systems at scale. This role combines backend service engineering and data platform engineering, with strong focus on reliability, performance, and cost efficiency in a cloud-native environment.

You will work on high-throughput APIs/services in Go, as well as data processing and workflow components in Python/Spark/SQL, partnering closely with product, platform, and data teams.

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  Design, build, and maintain backend services and data platform components.

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  Develop and optimize streaming and batch data workflows.

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  Improve reliability and operability (monitoring, alerting, incident prevention/recovery).

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  Improve data quality and consistency through schema/contracts and validation mechanisms.

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  Diagnose and resolve production issues across service and data layers.

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  Drive performance and cost optimization initiatives for large-scale workloads.

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  Collaborate across teams to deliver roadmap milestones.

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  Mentor engineers and contribute to engineering standards and review culture.

• 5+ years of software engineering experience in backend/data-intensive systems.

• Strong proficiency in Go (required).

• Strong proficiency in Python (required).

• Strong proficiency in SQL (required).

• Hands-on experience with distributed data systems (e.g., Kafka, Spark/Databricks).

• Experience operating services/pipelines in cloud production environments (GCP preferred).

• Solid understanding of reliability practices: observability, on-call, incident response.

• Strong communication and ownership; able to drive ambiguous projects to completion.

• Experience with Databricks/Delta Lake/Lakehouse architectures.

• Experience with Kubernetes/GKE and Terraform/IaC.

• Experience with data governance (lineage, access control, PII handling).

• Experience with identity/profile systems (entity resolution, merge logic).

• Experience with FinOps/cost optimization for platform workloads.

• Scala/Java experience for Spark ecosystem optimization is a plus.

Fluent in English.