Takeda
DataEngineerProfessionalII
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Engineer Professional II at Takeda. Skills: Data Engineering, Data Modeling, Cloud Technologies, AWS. Build and maintain data systems. Construct data tables and models”
What You'll Achieve.
Support business function requirements; Support downstream systems; Support digital product development; Foster data-driven decision-making; Ensure data accuracy and availability; Meet security and performance standards
Industry & Context.
Troubleshoot and resolve data-related issues
What They're Looking For.
Must Have
Bachelor's Degree from an accredited institution in Engineering, Computer Science, or a related field, 5+ years of experience in data engineering, software development, data warehousing, data lake/mesh, and supporting digital products developing data products following FAIR data principles, expertise in data integration, data modeling, and modern database technologies (GraphQL, SQL, No-SQL, python, pySpark) and AWS cloud technologies (e. g. , DMS, Lambda, SQS, Step Functions, Data Streaming), Databricks and/or Data Cloud/360 experience, Extensive experience in DBA, schema design & dimensional modeling, and SQL optimization, GenAI experience knowledge (Vectorization / RAG / MCP /. . ), Excellent written and verbal communication skills, with the ability to collaborate effectively with cross-functional teams, Understanding of good engineering practices (DevSecOps, source-code versioning using GIT,. . . ), Proficient working in AGILE SCRUM Teams and using JIRA and Confluence, Knowledge of SDLC, Proficiency with version control (e. g. , Git, GitHub, GitLab) and familiarity with CI/CD pipelines (e. g. , Jenkins, GitHub Actions), Good understanding of software security principles and secure coding practices, Knowledge of automated testing tools and frameworks and practices (unit testing, integration testing, E2E testing), Familiarity with relational and non-relational databases (PostgreSQL, MongoDB, DynamoDB), Knowledge of SDLC
Nice to Have
Experience with streaming technologies like Spark Streaming or Kafka, Experience in Agentforce360 or Agentforce platform, Infrastructure as Code (IaC) experience, preferably with Terraform, Experience designing and developing API data integrations using SOAP / REST / FAST
What You'll Do.
Build and maintain data systems
Construct data tables and models
Develop and maintain scalable data models
Develop and maintain data pipelines
Improve data models and quality
Implement data reconciliation processes
Ensure production data accuracy
Write unit test scripts
Write integration test scripts
Write performance test scripts
Perform data analysis
Troubleshoot and resolve data issues
Deploy data pipeline solutions
How You'll Work.
Team & Collaboration
Collaborate with business functions; Work closely with AGILE SCRUM Teams; Collaborate with enterprise teams; Partner with DevOps; Align with Data Trustees; Align with Data Stewards; Align with Master Data Management functions
Communication Scope
Excellent written communication skills; Excellent verbal communication skills
Full Job Description
By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s [Privacy Notice](https://jobs.takeda.com/privacynotice) and [Terms of Use](https://www.takeda.com/terms-and-conditions/). I further attest that all information I submit in my employment application is true to the best of my knowledge. ## **Job Description** **OBJECTIVES/PURPOSE** As a **Data Engineer Professional II** , you will be responsible for building and maintaining data systems and constructing data tables and data models that are optimized for operations and analysis, supporting several Business Function requirements and downstream systems. **ACCOUNTABILITIES** * Develop and maintain scalable data models and pipelines to support increasing data sources, volumes, and complexity. * Collaborate with several business functions to improve data models and its quality to support the development of digital products, fostering data-driven decision-making across the organization. * Implement processes and systems to ensure data reconciliation, monitor data quality, and ensure production data is accurate and available for key stakeholders, downstream systems, digital products, and business processes. * Write unit, integration, and performance test scripts, contribute to engineering documentation, and maintain the engineering wiki. * Perform data analysis to troubleshoot and resolve data-related issues. * Work closely with AGILE SCRUM Teams, specifically frontend and backend engineers, product managers, scrum masters, quality engineers to deliver integrated and scalable data products. * Collaborate with enterprise teams, including Enterprise Architecture, Security, and Enterprise Data Backbone Engineering, to design and develop data integration patterns and models supporting various digital products. * Partner with DevOps and the Cloud Center of Excellence to deploy data
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