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.