Engineering Manager, Data Ingestion

• Employment Status: Full-time
• Work Hours: Full Flextime (no core time)
• Office: Roppongi

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Organization/Team Mission

Engineering Principles:

• Passion For The Product
• Grow Together
• Solve Through Mechanisms
• Collaborate Openly

Data underpins decision-making across product, marketing, and machine learning. As Engineering Manager for the Data Ingestion Team, you will lead foundational systems that collect, process, and deliver high-volume event and operational data. You’ll drive technical strategy, people leadership, and operational health in partnership with Data Management, BI Analytics, SRE, and Platform Engineering.

You will interact and collaborate with:

• Data Management Team
• Data Analytics Teams
• Machine Learning Teams (Search, Recommendation, Credit, Anti-Fraud, etc.)
• Product Teams (Marketing, CRM, Customer Support, Anti-Fraud, etc.)

These partnerships enable reliable, scalable, and timely data delivery for analytics, experimentation, machine learning, and business decision-making.

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Work Responsibilities

Team Leadership & People Management

• Lead, mentor, and grow a team of Data Ingestion Engineers.
• Foster a culture of psychological safety, operational excellence, ownership, and continuous improvement.
• Support engineers through coaching, performance management, career development, and technical mentorship.
• Hire and onboard engineers to strengthen team capability and diversity.
• Manage execution planning, prioritization, and delivery of roadmap initiatives.

Technical Strategy & Platform Ownership

• Define and drive the long-term technical vision and roadmap for data ingestion.
• Lead architectural discussions and technical decision-making for large-scale distributed data systems.
• Drive improvements in scalability, reliability, maintainability, and developer productivity.
• Partner with stakeholders to align platform investments with company-wide data strategy and goals.
• Establish engineering standards, operational practices, and self-service ownership.

Reliability, Operations & Cost Optimization

• Oversee the reliability and operational health of mission-critical ingestion pipelines and event processing systems.
• Lead incident management and post-incident reviews for high-severity production issues.
• Drive improvements in observability, SLIs/SLOs, monitoring, and operational readiness.
• Partner with FinOps and infrastructure teams to optimize platform costs.
• Improve resource efficiency through partitioning, clustering, right-sizing, storage lifecycle management, and pipeline optimization.

Unique Challenges

• Maintain a high-volume, mission-critical platform with a lean team; ensure a reliable self-service model for backend teams.
• Expand ingestion coverage to third-party, unstructured, and company-wide data sources (e.g. HR, Finance).
• Help drive Data × AI initiatives.

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Qualifications

Required

• Shared belief in mission and values.
• Experience writing design documents or technical proposals and aligning with stakeholders.
• Experience designing, developing, and operating large-scale services/distributed systems or data pipelines using Go, Python, Java, Scala.
• Excellent communication skills to collaborate and explain technical risks to non-technical leadership.

Preferred

• Experience with streaming data processing frameworks (Apache Beam, Spark, Flink).
• Experience with Data Warehouse technologies (BigQuery, Redshift, Hive/Hadoop, Snowflake).
• Familiarity with monitoring and alerting tools.
• Experience with Google Cloud Platform (Dataflow, Pubsub, Kubernetes Engine, Compute Engine).
• Experience with Confluent Cloud or Apache Kafka.
• Experience with workflow engines (Argo Workflow, Apache Airflow).
• Experience publishing/contributing to OSS.

Language Requirements

• English: Independent (CEFR - B2)
• Japanese: Independent (CEFR - B2)
  About CEFR

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Learn More

• Careers site
• Mercan
• Social Media: X / Linkedin
• Data Processing overview (JP)
• Data Streaming for server side logging (JP)
• Data Processing batch pipeline overview (JP)
• Data Processing Change Data Capture (JP)

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Recruiting Process

• Application screening
• Skill assessment (HackerRank or GitHub for engineering; varies for others)
• Interview (number of interviews varies)
• Reference check
• Offer

Learn more about our recruiting process.

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Equal Opportunity

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