【Purpose & Scope】 As a Senior Data Engineer, you will play a crucial role in designing, building, and maintaining our data infrastructure. Your expertise in Databricks, PySpark, SQL and other related technologies, will be instrumental in driving data-driven decision-making across the organization. You will play a pivotal role in building maintaining and enhancing our systems across the organization. This is a fantastic global opportunity to use your proven agile delivery skills across a diverse range of initiatives, utilize your development skills, and contribute to the continuous improvement/delivery of critical IT solutions.
【Essential Job Responsibilities】 (雇入れ直後)
Data Pipeline Development:
Design, build, and optimize data pipelines using Databricks and PySpark. Ensure data quality, reliability, and scalability.
Application Transition:
Support the migration of internal applications to Databricks (or equivalent) based solutions. Collaborate with application teams to ensure a seamless transition.
Mentorship and Leadership:
Lead and mentor junior data engineers. Share best practices, provide technical guidance, and foster a culture of continuous learning.
Data Strategy Contribution:
Contribute to the organization's data strategy by identifying opportunities for data-driven insights and improvements.
- Participate in smaller focused mission teams to deliver value driven solutions aligned to our global and bold move priority initiatives and beyond.
- Design, develop and implement robust and scalable data analytics using modern technologies.
- Collaborate with cross functional teams and practises across the organisation including Commercial, Manufacturing, Medical, DataX, GrowthX and support other X (transformation) Hubs and Practices as appropriate, to understand user needs and translate them into technical solutions.
- Provide Technical Support to internal users troubleshooting complex issues and ensuring system uptime as soon as possible.
- Champion continuous improvement initiatives identifying opportunities to optimise performance security and maintainability of existing data and platform architecture and other technology investments.
- Participate in the continuous delivery pipeline. Adhering to DevOps best practises for version control automation and deployment. Ensuring effective management of the FoundationX backlog.
- Leverage your knowledge of data engineering principles to integrate with existing data pipelines and explore new possibilities for data utilization.
- Stay-up-to-date on the latest trends and technologies in data engineering and cloud platforms.
【Specific Physical or Environmental Requirements】
- Permanent position.
Remote/ Hybrid:
candidates must be located within commutable distance from the office.
- Astellas is a global company. Successful candidates will be expected to work across different time zones and according to regions or specific locations based upon demand.
- At Astellas we recognize the importance of work/life balance, and we are proud to offer a hybrid working solution allowing time to connect with colleagues at the office with the flexibility to also work from home. We believe this will optimize the most productive work environment for all employees to succeed and deliver. Hybrid work from certain locations may be permitted in accordance with Astellas' Responsible Flexibility Guidelines.
Subject Matter Expertise:
possess a strong understanding of data architecture/ engineering/operations/data model (e.g. data vault, dimensional data model).
- Experience within Life Sciences/ Pharma /Manufacturing industry is preferred.
- Proven experience in building robust data pipeline; experience in (near) real-time processing is preferred.
Technical Proficiency:
Strong coding skills for example, Python, PySpark, SQL.
- Experience in Databricks or Change Data Capture (eg. Fivetran) is preferred. Other technologies include Oracle and APEX.
- Proven experience with data analytics practices and techniques and organizations
Agile Practices:
Experience working in Agile development environments, participating in sprint planning, stand-ups, and retrospectives.
Cloud Data Solutions:
Familiarity with other cloud platforms (AWS, Azure, Google Cloud) and their data services
Analytical Thinking:
Demonstrated ability to lead ad hoc analyses, identify performance gaps, and foster a culture of continuous improvement
Agile Champion:
Adherence to DevOps principles, automation, and a proven track record with CI/CD pipelines for continuous delivery
- Understand and Interpret business requirements and can term them into technical requirements.
- Minimum 5 years experience in data engineering with a strong understanding of PySpark and SQL, building data pipelines and optimization.
- Minimum 5 years experience in data engineering and integration tools (e.g., Databricks, Change Data Capture)
- Minimum 5 years experience of utilizing cloud platforms (AWS, Azure, GCP). A deeper understanding/certification of
AWSand Azure is considered a plus. - Experience with relational and non-relational databases.
For example:
- AWS certified DevOps engineer (Professional),
- AWS Certified Developer (Professional)
- Mulesoft Certified integration architect Level 1 (Essential),
- Microsoft Certified Azure Integration and Security.
- Proficient in RESTful APIs
- AWS, CDMP, MDM, DBA, SQL, SAP, TOGAF, API, CISSP, VCP (any relevant certification)
- Understanding of MuleSoft's Anypoint Platform and its components
- Experience with designing and managing API-led connectivity solutions
- Knowledge of integration patterns and best practices
- Proficiency in network architecture and security concepts
AWS
- Experience provisioning, operating, and managing
AWSenvironments - Experience developing code in at least one high-level programming language
- Understanding of modern development and operations processes and methodologies
- Ability to automate the deployment and configuration of infrastructure using
AWSservices and tools - Experience with continuous integration and continuous delivery (CI/CD) methodologies and tools
- Fundamental understanding of Microsoft Azure and its services
- Experience with Azure services related to computing, networking, storage, and security
- Knowledge of general IT security principles and best practices
- Understanding of cloud integration patterns and Azure integration services such as Logic Apps, Service Bus, and API Management
Subject Matter Expertise:
possess a strong understanding of data architecture/ engineering/operations/ reporting within Life Sciences/ Pharma industry across Commercial, Manufacturing and Medical domains.
- Other complex and highly regulated industry experience will be considered across diverse areas like Commercial, Manufacturing and Medical.
Data Analysis and Automation Skills:
Proficient in identifying, standardizing, and automating critical reporting metrics and modelling tools
Analytical Thinking:
Demonstrated ability to lead ad hoc analyses, identify performance gaps, and foster a culture of continuous improvement.
Technical Proficiency:
Strong coding skills in SQL, R, and/or Python, coupled with expertise in machine learning techniques, statistical analysis, and data visualization.
Agile Champion:
Adherence to DevOps principles and a proven track record with CI/CD pipelines for
【Other critical skills required】
Cross-Cultural Experience:
Work experience across multiple cultures and regions, facilitating effective collaboration in diverse environments.
Innovation and Creativity:
Ability to think innovatively and propose creative solutions to complex technical challenges.
Global Perspective:
Demonstrated understanding of global pharmaceutical or healthcare technical delivery, providing exceptional customer service and enabling strategic insights and decision-making.
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