Ingeniero Senior, Datos Industriales

Job Description

Ciudad de México

Nivel de Estudios

Bachelor’s Degree in Computer Science or Computer Engineering. Advanced degree preferred.

Experiencia Requerida

5+ years delivering enterprise-level Data Engineering solutions

Habilidades

Soft Skills

• Team Player: Excellent communication and interpersonal skills, working effectively as part of a team and collaborating with stakeholders across different locations.
• Adaptability: Thrive in a dynamic, fast-paced work environment and adapt quickly to changing business needs.
• Attention to Detail: Meticulous attention to detail, ensuring data accuracy and maintaining high-quality standards in all deliverables.

Technical Skills

• A minimum of 5 years of professional hands-on experience with data engineering and data management
• An understanding of cloud infrastructure
• Strong problem-solving skills and the ability to troubleshoot complex data-related issues
• Solid understanding of data modeling, data warehousing, data governance and ETL processes
• Proficiency in Python and SQL/NoSQL query languages (ability to learn others)
• Experience deploying software using cloud-based solutions in AWS, Azure, or similar
• Familiarity with OPC-UA, MQTT, and industrial automation protocols is a significant advantage
• Experience in a manufacturing or industrial environment preferred

Resumen

You will partner collaboratively with business and technical stakeholders to design, build, and maintain data pipelines and architectures that ingest, store, and analyze data from industrial systems (PLC, SCADA, IoT). The data will bridge OT (Operational Technology) and IT by optimizing ETL processes, ensuring data quality, and enabling decision support initiatives to improve manufacturing efficiency. You will ensure polices, processes, and governance standards are adhered to so that consistent and trusted data can drive business initiatives and enable data driven decision making in a reliable, repeatable, and scalable way. You will be responsible for the entire project life cycle from conception through commissioning of projects that support business initiatives such as Overall Equipment Effectiveness (OEE), Key Performance Indicators (KPIs), self-service Business Intelligence (BI) projects, Data Contextualization, Industrial Data Fabric, Machine Learning/AI use cases and ad-hoc analytics.

Responsabilidades

1.Data Pipeline Development - Create, maintain, and optimize scalable, reliable data pipelines for structured, unstructured, batch and real-time data using API's, Python, SQL and NoSQL.
2. Industrial Data Integration - Extract and clean data from PLC (Programmable Logic Controllers), HMI (Human Machine Interface), and SCADA systems
3. ETL/ELT Processes - Design and implement robust processes to extract, transform, and load data from manufacturing systems into secure, structured, or unstructured storage solutions (Data Lakes/Warehouses).
4. Performance Optimization - Redesign infrastructure for greater scalability and automate manual data processes.
5. Data Integrity & Security: Ensure data quality through testing, validation, and adherence to security protocols.

6. Collaboration & Support - Work with Production Engineering, Data Science, and Business Intelligence teams to understand
data requirements and ensure the availability of clean, high-quality data for analysis and reporting. Troubleshoot and
resolve data-related issues and performance bottlenecks in a timely manner.
7. Governance - Maintain data warehouse and respective governance that is used by operations stakeholders, business intelligence customers and data science teams. Produce and maintain high-quality documentation to ensure transparency and understanding of solutions. Implement, achieve and maintain strong data governance including technical data catalog, business data catalog, data lineage and data quality.
8. Analytic Life Cycle Management - Estimate, architect, and execute on delivery of critical data solutions. Manage life cycle from conception through commissioning of projects that support business initiatives such as Overall Equipment
Effectiveness (OEE), Key Performance Indicators (KPI) development, Self-service Business Intelligence (BI) Projects, Data Contextualization, Industrial Data Fabric, Machine Learning and AI use cases and ad-hoc analytics.

Location

Additional Locations

Job Type

Job Area

Equal Opportunity

Constellation Brands is committed to a continuing program of equal employment opportunity. All persons have equal employment opportunities with Constellation Brands, regardless of their sex, race, color, age, religion, creed, sexual orientation, national origin or citizenship, ancestry, physical or mental disability, medical condition (cancer or genetic characteristics), marital status, gender (including gender identity or gender expression), familial status, military or veteran status, genetic information, pregnancy, childbirth, breastfeeding, or related conditions (or any other group or category within the framework of the applicable discrimination laws and regulations).