Data Engineer
Company
Panalyt is a people analytics SaaS company that helps organizations make better people decisions through meaningful data and insights.
Our platform helps companies reduce attrition, improve recruitment, identify gender diversity and pay gaps, strengthen employee engagement, and improve team performance.
Headquartered in Japan, we have operated as a remote-first company from day one. Our engineering team works closely with product, data science, and business teams to build reliable, scalable, and customer-focused systems.
About the Role
As a Data Engineer at Panalyt, you will design, build, and operate the data infrastructure that powers our people analytics platform.
HR data is inherently complex. Different companies, systems, and regions structure and define workforce data differently, often with inconsistent formats, missing values, and ambiguous business logic. Your work will directly shape the accuracy, reliability, and usefulness of the insights our customers depend on.
This role sits at the core of our product. You will own technical integrations with our clients, from understanding and modeling their data to building resilient ingestion pipelines and maintaining reliable production systems over time.
Because we are a startup, responsibilities are intentionally flexible rather than narrowly defined. You will be encouraged to take ownership wherever you can create impact, whether that involves infrastructure, tooling, operational improvements, product collaboration, or customer-facing problem solving. Depending on your experience, you may also mentor other engineers and contribute to technical direction.
What You’ll Do
You will be responsible for:
- Designing, developing, and operating data pipelines and ETL / ELT workflows
- Building integrations with HR SaaS platforms and other business systems, including API connector development
- Designing and improving scalable data models in collaboration with product, data science, and business teams
- Building systems for data validation, monitoring, anomaly detection, and observability
- Supporting client onboarding through data mapping, cleansing, transformation, and quality assurance
- Improving infrastructure reliability, scalability, availability, and cost efficiency
- Developing internal tools that improve operational efficiency and developer productivity
- Supporting QA and debugging for product features where data correctness is critical
- Documenting pipelines, infrastructure, operational processes, and technical decisions
- Identifying and implementing improvements in automation, delivery processes, and system architecture
Minimum Qualifications
- Bachelor’s degree in Computer Science, Data Engineering, Data Analytics, or a related field
- 2+ years of experience in data engineering or a related role
- Business-level English
- Experience with Python and SQL
- Strong analytical and problem-solving skills
- Ability to work independently in a remote-first environment
- Strong attention to detail and reliability in execution
- Ability to manage multiple priorities with limited supervision
Preferred Qualifications
- Experience with cloud platforms such as AWS, GCP, or Azure
- Experience with Docker and Kubernetes
- Experience with orchestration tools such as Apache Airflow
- Experience building and operating production-grade data pipelines
- Experience working with messy, multi-source business data
- Experience designing data quality, monitoring, or anomaly detection system
- Business-level fluency in Japanese
- Experience working in startups or fast-moving product environments
Benefits
- ✅ Remote-first work style with flexibility to work from locations that overlap reasonably with Japan time zones
- ✅ Flexible working hours focused on outcomes and collaboration
- ✅ Choice of preferred hardware and software, including laptop, monitor, OS, and IDE
- ✅ Restricted Stock Units (RSUs) so team members can participate in the company’s long-term success
- ✅ Unlimited vacation with responsible coordination and communication
