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**Data Engineer**
**Colonia Napoles, Mexico**
**At Getinge we have the passion to perform**
Join our diverse teams of passionate people and a career that allows you to develop both personally and professionally. At Getinge, our passion is to secure that every person and community have access to the best possible care, offering hospitals and life science institutions products and solutions that aim to improve clinical results and optimize workflows. Every day we collaborate to make a true difference for our customers - and to save more lives.
Are you looking for an inspiring career? You just found it.
As a Data Engineer at Getinge, you will play a pivotal role in advancing our Cloud Data Platform. Your skills will power the implementation of robust data ingestion pipelines, data cleansing procedures, analytical notebooks, and advanced storage solutions - all crucial building blocks in our cutting-edge Data Science and GenAI platform.
You will work alongside product managers, business data owners, machine learning and GenAI experts, and data consumption teams, all working together to deliver never before possible insights to the business. Your contributions will be essential for our Digital initiatives, including Data Governance protocols, DevOps planning, cost & performance optimization, and ensuring for disaster recovery. You will contribute to integration of our data solutions with machine learning models and LLMs, facilitating advances in our AI-driven insight capabilities. You will also engage in special projects that will help grow the Digital Quotient of our organization.
**Benefits**:
- Food vouchers: $3,300 monthly
- Christmas Bonus (aguinaldo): 30 days
- Vacation: 20 days
- Vacation bonus: 30%
- Savings Fund 2.5% on gross salary (capped)
- Support for teleworking for reimbursement 9,5000
- Support for teleworking (electricity and internet) $500.00 mxp per month
- Mayor Health Insurance (SGMM) for employee, spouse and child(ren)
- Life insurance
- Telemedicine for employees and five additional people
- Parking inside the WTC
**The qualified applicants will be responsible for the following**:
- Data Solutions: Design, refine and maintain scalable data structures that meet business requirements, select appropriate connectors for various source systems, identify data cleansing logic, ship features to Machine Learning consumers, and implement data access solutions for analytical and reporting consumption.
- Data Pipeline and Storage: Develop, orchestrate, and maintain data flows and Extract, Transform, Load (ETL) procedures using Azure Synapse or similar pipeline tools; implement analytical processing using DataBricks or similar analytics tools; and implement cloud storage using blob storage, relational, NoSQL, and vector databases.
- Data Security and Compliance: Enforce adherence to all global data privacy and security regulations and best practices. Identify and report compliance breaches, and contribute to development of platform solutions to safeguard data privacy.
- DevOps and Data Governance: Participate in the development and operation of a DevOps framework to facilitate Continuous Integration/Continuous Deployment (CI/CD) for data processes. Contribute to the design & maintenance of Data Governance tools that enable the organization to effectively catalog and manage data assets.
- Troubleshooting and Performance Optimization: Identify and resolve data processing issues and inefficiencies to ensure optimal system performance and data accuracy. Implement optimizations to enhance data processing efficiency while minimizing costs.
- Troubleshooting and Performance Optimization: Identify and resolve data processing issues and inefficiencies to ensure optimal system performance and data accuracy. Implement optimizations to enhance data processing efficiency while minimizing costs.
- Collaborating with AI research teams to ensure data quality and accessibility for building state-of-the-art models, including generative AI and deep learning algorithms.
- Bachelor’s Degree in Computer Science or Information Systems, or equivalent combination of education and work experience.
- A minimum of 2 years of experience as a Data Engineer.
- Proven experience of a minimum 1 year with Azure Cloud Services, including Azure Synapse Analytics, Azure Databricks, Azure Data Lake Storage, and others.
- Proficiency in SQL, Python, and other relevant data analytics languages.
- Knowledge of data analytics and visualization tools (e.g., Power BI, Tableau) is desirable.
- Understanding of GenAI/LLM solutions and/or Machine Learning
- Knowledge of data pipeline workflow management, and ETL tools
- Experience in designing and implementing data ingestion and storage systems
- Understanding of data structures, data modeling, and software architecture. Experience with DevOps processes and tools.
- Familiarity with data governance protocols and data quality assurance processes.
- Familiarity with performance optimizatio
