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About the Role
The IT EDP Data & Analytics team is seeking a talented and experienced Data Engineer to build and enhance reliable, scalable data products that enable high-impact insights, accelerate decision-making, and improve patient outcomes. This individual will play a key role in delivering a modern data ecosystem across cloud and enterprise platforms, driving change, championing continuous improvement, and thriving in a fast-paced environment.
Responsibilities
- Design, build, and maintain end‑to‑end data pipelines and integrations to support HP Commercial Data & Analytics use cases.
- Develop, operate, and optimize integrations using SnapLogic and AWS services (S3, Lambda, Glue) and Apache Airflow.
- Implement and maintain analytics‑ready data models in Snowflake, ensuring performance, scalability, and cost‑efficient design.
- Build transformation logic and analytics layers using dbt, including modular modeling, testing, documentation, and deployment best practices.
- Contribute to and enforce data governance standards using Collibra, ensuring metadata quality, lineage, ownership, and consistent definitions.
- Partner with Data Quality stakeholders to implement and monitor quality controls using Attaccama, including rules, profiling, exception handling, and remediation workflows.
- Support data lifecycle processes and operationalization of data products to align delivery with platform and product standards.
- Proactively identify opportunities to simplify architecture, automate repetitive work, and reduce operational effort.
- Ensure all solutions follow security, privacy, and compliance expectations.
- Collaborate closely with Product Owners, Data Scientists, Analysts, Architects, and business stakeholders to translate needs into reliable, reusable data assets.
- Act as a role model for engineering excellence: version control, CI/CD, code reviews, documentation, and operational runbooks.
Requirements
- Degree in Computer Science, Engineering, Data/Information Systems, or a related field.
- 4+ years of relevant experience in data engineering, analytics engineering, or similar roles.
- Hands‑on experience building integrations and pipelines using tools such as SnapLogic (or comparable iPaaS) and cloud services (AWS S3, Lambda, Glue), and Apache Airflow.
- Strong experience with Snowflake including data modeling, performance tuning, and secure data access patterns.
- Proven experience with dbt (models, tests, macros, documentation, environments, CI/CD integration).
- Familiarity with data governance and metadata management, ideally with Collibra; understanding of lineage, stewardship, and data catalog practices.
- Experience implementing data quality controls and monitoring, ideally with Attaccama (or equivalent tooling and approaches).
- Solid knowledge of software engineering fundamentals: Python/SQL, Git, coding standards, automated testing, and production support practices.
- Demonstrated ability to work independently, manage priorities, and proactively drive work forward in a dynamic environment.
- Strong stakeholder management, analytical thinking, and structured problem‑solving skills.
- Excellent communication skills in English and Japanese.
Skills
- SnapLogic
- AWS S3
- AWS Lambda
- AWS Glue
- Apache Airflow
- Snowflake
- dbt
- Collibra
- Attaccama
- Python
- SQL
- Git
- CI/CD
- Data Modeling
- Performance Tuning
- Data Governance
- Metadata Management
- Data Quality
- Automated Testing
- Version Control
Experience Level
- 4+ years of relevant experience
Education Level
- Degree in Computer Science, Engineering, Data/Information Systems, or a related field