Software Engineer Data Infrastructure

About the Job

1. 1As a Data Infrastructure Engineer, you’ll take ownership of designing, building, and optimizing high-performance data infrastructure and pipelines.
2. 2You’ll work on transforming raw, unstructured data into reliable, scalable, and accessible systems that support key business initiatives and data products.
3. 3Architect and implement large-scale data systems to ensure high performance, reliability, and scalability.
4. 4Enhance ETL processes, ensuring efficient data movement, quality, and availability.
5. 5Establish and maintain data quality standards, automated validation, and monitoring for data integrity.
6. 6Identify and experiment with new technologies, driving innovation and tool selection for scalable solutions.
7. 7Lead by example, mentoring junior engineers, and sharing best practices to elevate the team’s technical capabilities.
8. 8Work closely with data scientists, analysts, and product teams to define infrastructure needs and support data-driven decision-making.

応募資格（必須）

• Hands-on experience with at least one major cloud platform (GCP preferred, AWS, or Azure), including infrastructure components like storage (e.g., BigQuery, S3), compute resources (e.g., Kubernetes, Dataproc), and networking.
• Strong proficiency in one or more programming languages (Python, Java, or Scala) with experience building complex data processing solutions.
• Advanced SQL skills, including query optimization and data warehousing techniques for high-volume data environments.
• Familiarity with big data frameworks and tools, such as Apache Spark, Hadoop, or Kafka, and experience implementing both batch and real-time processing solutions.
• Proven track record of designing and building ETL/ELT processes and data workflows for high-volume data in production environments.
• Understanding of data governance practices, data quality management, and setting up automated validation and monitoring for data integrity.

歓迎する経験

• Deep knowledge of distributed systems, including understanding of scalability, fault tolerance, and reliability in data systems, with hands-on experience in technologies like Spark, Flink, or Kafka Streams.
• Experience with workflow orchestration tools like Apache Airflow or Google Cloud Composer for managing complex data pipelines and automated workflows.
• Proficiency in containerization and orchestration (e.g., Docker, Kubernetes) and familiarity with DevOps practices for CI/CD, automation, and deployment in cloud environments.
• Familiarity with data security best practices, including data encryption, role-based access control, and industry compliance standards (e.g., GDPR).
• Experience with data monitoring, logging, and alerting tools (e.g., Prometheus, Grafana, DataDog) to ensure data infrastructure reliability and performance.
• Experience leading technical projects or initiatives, with a demonstrated ability to make architectural decisions, mentor junior engineers, and drive best practices across teams.

待遇・福利厚生

• DC
• 団体長期障害所得補償保険
• 年間休日120日
• 提携サービス優待

求めるスキル・経験