Software Engineer_Data Infrastructure

About the Job

1. 1Architect and implement large-scale data systems to ensure high performance, reliability, and scalability.
2. 2Enhance ETL processes, ensuring efficient data movement, quality, and availability.
3. 3Establish and maintain data quality standards, automated validation, and monitoring for data integrity.
4. 4Identify and experiment with new technologies, driving innovation and tool selection for scalable solutions.
5. 5Lead by example, mentoring junior engineers, and sharing best practices to elevate the team’s technical capabilities.
6. 6Work closely with data scientists, analysts, and product teams to define infrastructure needs and support data-driven decision-making.

Why Join Us

1. 1Lead critical infrastructure projects, shaping the future of data at Macromill.
2. 2Handle vast amounts of data in both streaming and batch environments, playing a key role in turning raw, unstructured data into valuable business insights.
3. 3Experiment with and implement cutting-edge technologies, driving rapid iteration and innovation in data systems.
4. 4Work with state-of-the-art tools, cloud platforms, and big data frameworks to build scalable, high-performance infrastructure.
5. 5Opportunities for leadership, mentorship, and professional development in a fast-evolving environment.
6. 6Represent Macromill at technical events, building both your personal brand and the company’s reputation within the tech community.

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

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求めるスキル・経験