Description

Data Engineer
Location: Mexico (Mexico City, Guadalajara, Monterrey) - Hybrid as per Infosys Mexico policy (CST time)

Role Overview
Data Engineers design and build scalable data pipelines using tools like Azure Data Factory, Synapse, and Databricks. Manage data storage, transformation, and integration while ensuring data quality, security, and compliance. Collaboration with cross-functional teams and implementing best practices in DevOps, governance, and performance tuning are key to success.

Key Responsibilities

• Design and implement data storage solutions.
• Create and maintain data storage solutions including Azure SQL Database, Azure Data Lake, and Azure Blob Storage.
• Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure Create data models for analytics purposes
• Utilizing Azure Data Factory or comparable technologies, create and maintain ETL (Extract, Transform, Load) operations
• Use Azure Data Factory and Databricks to assemble large, complex data sets
• Implementing data validation and cleansing procedures will ensure the quality, integrity, and dependability of the data.
• Ensure data security and compliance
• Optimize Azure SQL databases for efficient query performance
• Collaborate with data engineers, and other stakeholders to understand requirements and translate them into scalable and reliable data platform architectures
• Participate in all scrum ceremonies

Basic Qualifications

• Bachelor's degree or foreign equivalent in Computer Science or related field.
• 7+ years of IT experience , including data engineering and cloud solutions.
• English - strong verbal and written communication.
• Proven experience implementing Azure services in enterprise environments.
• Knowledge of infrastructure (networking, storage, hardware optimization).

Mandatory Skills

• Azure Certification : Solutions Architect, Developer
• Hands-on experience with: ADF, Synapse Analytics, Data Lake storage, SQL database / SQL server, Azure Databricks
• Python, PySpark
• ETL and Pipeline designs

Preferred Skills

• Blend of technical expertise, analytical problem-solving, and collaboration with cross-functional teams
• Azure DevOps
• Apache Spark, Python
• SQL proficiency
• Data modeling
• ETL processes
• Azure Databricks knowledge
• Familiarity with data warehousing
• Big data technologies
• Data governance principles

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Other Requirements

• Ability to work under tight timelines and manage complex requirements.
• Flexible to work extended hours if needed.
• Self-motivated, proactive, and a strong team player.