Engineering Manager (Data Platform)

Responsibilities and Duties

1. 1Manage and lead a team of 4–8 engineers, providing guidance, mentorship, and support to foster professional growth.
2. 2Develop and maintain a high-performing and motivated engineering team.
3. 3Establish and communicate clear team goals, expectations, and deliverables.
4. 4Maintain a ratio of 7:3 between team and technical management, ensuring a balance between leadership and hands-on technical contributions.
5. 5Drive design and implementation of robust data pipelines, ingestion frameworks, and transformation systems.
6. 6Define and enforce best practices for data modeling, data quality, schema management, and performance optimization.
7. 7Ensure high availability, scalability, and reliability of data systems handling large-scale workloads.
8. 8Define and manage SLAs/SLOs for data pipelines (freshness, latency, accuracy).
9. 9Translate business requirements into scalable and maintainable data platform designs.
10. 10Drive cloud infrastructure strategy for data platform (cost optimization, scalability, performance).
11. 11Evaluate and adopt new tools and technologies aligned with platform strategy.
12. 12Ensure data governance, security, and compliance requirements are met.
13. 13Manage project timelines, priorities, and resource allocation to ensure timely delivery.

Work Environment

1. 1Provided PC Specs: We provide PCs equipped with the latest CPUs (MacOS or Windows). Custom-made PCs tailored to business requirements and replacements with the latest OS are also possible.
2. 2Systems to Enhance the Development Environment: Peripheral devices necessary for work (such as displays, mice, keyboards) can be purchased as office supplies. Generally, you can choose from standard products (catalog), and if conditions are met, you can apply for non-standard products as well. (*Excluding certain group companies)
3. 3Money Forward Library: We have a library system where you can freely borrow books, ranging from technical books to management books. Desired books can be purchased at the company's expense.
4. 4Referral Driven: We cover the cost of recruitment meals. There is a referral reward system.
5. 5Conference Participation Support: The company partially covers participation in domestic and international conferences, such as RubyKaigi and Google I/O.

Selection Process２

1. 1Money Forward may ask for your cooperation with reference checks using a reference check service tool.
2. 2We would like to gather information about you from your supervisor and colleagues at your current or former company to ensure a more reliable match and facilitate your early success after joining our company.
3. 3We do not make employment decisions based solely on the contents of reference checks.
4. 4The fact that you are in the selection process with us will not be disclosed to referees.

応募資格（必須）

• Bachelor’s degree in Computer Science, Software Engineering, or a related field (or equivalent experience).
• At least 3+ years of engineering management experience.
• At least 5+ years of hands-on experience building and operating high-volume data platforms.
• Prior experience in a high-scale SaaS or data-intensive product company.
• Strong programming background (e.g., Python, Java, Scala, or Go).
• Strong hands-on experience with: Data pipelines (batch and streaming), ETL/ELT frameworks, Data warehouses and OLAP systems, Real-time streaming (Kafka Streams, Flink, Spark Streaming or similar)
• Experience with tools such as: Apache NiFi, Kafka, RabbitMQ, ClickHouse, Snowflake (or similar)
• Experience working with cloud platforms (AWS, Azure, etc.).
• Deep understanding of distributed systems and data architecture patterns.
• Experience in designing scalable, fault-tolerant, and high-throughput systems.

歓迎する経験

• Experience with: Data lake/lakehouse architectures (e.g., Delta Lake, Iceberg), Workflow orchestration tools (Airflow, Dagster, Argo)
• Knowledge of data security and compliance (GDPR, SOC2, etc.).
• Experience supporting ML/AI data pipelines and feature engineering workflows.
• Experience implementing data quality, lineage, and governance frameworks.
• Experience building internal data platforms as a product (self-serve data platforms).
• Experience in AI development and/or experience in using AI tools to improve development processes.

待遇・福利厚生

• インフルエンザ予防接種
• ご近所手当
• 家賃給与控除制度
• 提携サービス優待

求めるスキル・経験