Job Description Summary

Data Engineer responsible for supporting production data platforms and customer-facing solutions. The role focuses on troubleshooting and resolving support tickets and production issues, gathering and refining requirements, and implementing and testing new data engineering solutions. Key responsibilities include designing and maintaining data access layers for reporting and analytics, performing data profiling and analysis across source and target systems, and developing a strong understanding of metadata and underlying data structures to standardize data load processes. The position involves building, automating, and testing ETL jobs based on data mapping specifications, executing complex data loads and transformations using multiple tools and technologies, validating data mapping results against expected outcomes, and applying defined data quality rules to ensure accurate, reliable, and consistent data for business use.

Job Description

Job Description

Roles and Responsibilities

In this role you will:

• Provide operational support by troubleshooting, monitoring, and resolving customer support tickets and production issues.

• Participate in requirement gathering processes and work in implementing and testing new data engineering solutions to address customer needs.

• Implement data access layers for reporting, data analysis, metadata management and data services. 

• Contribute to continuous improvement initiatives to enhance data engineering processes and products.

• Leverage technical data dictionaries and business glossaries to analyze the datasets

• Perform data profiling and data analysis for any source systems and the target data repositories.

• Develop an understanding of metadata and underlying data structures to standardize data load processes.

• Perform a variety of data loads & data transformations using multiple tools and technologies.

• Build and test automated Extract, Transform & Load (ETL) jobs based on data mapping specifications.

• Validate data mapping results and ensure alignment with expected outcomes.

• Apply and ensure Data Quality (DQ) rules provided by the team.

Basic Requirements

• Bachelor's Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with intermediate experience.

• Able to legally work in Mexico. We will not sponsor individuals for employment visas, now or in the future for this job.

• Foundational knowledge of storage architecture, data modeling, data management, and data processing techniques.

• Hands-on experience in writing SQL scripts for SQLServer, Oracle, MySQL, or PostgreSQL.

• Hands-on experience in scripting and programming languages like C#, Powershell and Python, including version control of the code.

• Basic understanding of Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) data models.

• Hands-on experience to structure and unstructured datasets and handling XML, JSON file formats, etc.

• Hands-on experience to Extract, Transform & Load (ETL) tools or ELT tools.

• Exposure to data patterns using regular expressions.

• Exposure to data analytics to identify data patterns and detect issues in data.

Desired Expertise:

• Exposure to Azure cloud services: Devops, Storage, Document Intelligence

• Exposure to AI Tools: Copilot, Devin AI, or Claude Sonet, etc.

• Exposure to Data visualization tools: Tableau, PowerBI or others.

• Understanding of aerospace industry practices: Aircraft maintenance.

• Awareness of Lean manufacturing or Six Sigma principles.

Domain Expertise:

• Exposure to batch processing and audit datasets from industrial businesses

• Knowledge of industrial applications in a commercial/finance/industrial/manufacturing settings.

• Exposure to customer service and accounting customer data domains.

Leadership skills:

• Effective communication and interpersonal skills: Written and oral, in English and Spanish.

• Collaborative mindset: Partner with team members to understand project objectives and resolve technical issues.

• Clear communication: Share project status or challenges concisely with cross-functional teams.

• Initiative and innovation: Identify opportunities for improvement and experiment with new software frameworks.

• Adaptability: Pivot quickly to new environments and changing requirements.

• Problem-solving mindset: Explore alternative solutions and provide in-depth scenario analyses.

Additional Information