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Data Engineer | Staff or Non-line Manager | IT Enterprise Data & Platforms Japan
The Position
Our IT EDP Data & Analytics team is seeking a talented and experienced Data Engineer. The ideal candidate will be responsible for building and enhancing 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. With a strong engineering mindset, the individual will drive change, champion continuous improvement, and thrive in a fast-paced environment with evolving priorities.
Tasks and 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 such as S3, AWS Lambda, and AWS Glue, and Apache Airflow to ensure robust ingestion, transformation, and orchestration.
- 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 by leveraging tools such as 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 (as applicable in the ecosystem) to align delivery with platform and product standards.
- Proactively identify opportunities to simplify architecture, automate repetitive work, and reduce operational effort (observability, alerting, self‑healing patterns).
- Ensure all solutions follow security, privacy, and compliance expectations (e.g., regulated environment practices, audit readiness, access controls, data handling).
- 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, with 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 — specifically AWS S3, Lambda, and 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, enabling clear interaction with technical and non‑technical stakeholders.
Nice to have
- Experience with regulated environments (e.g., GxP), validation, audit readiness, or privacy‑by‑design implementation.
- Familiarity with data platform observability (pipeline monitoring, data drift, SLAs/SLOs)
- Exposure to domain data in pharmaceutical commercial areas.
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