Lead Azure Data Engineer

Lead Azure Data Engineer (Ingeniero líder de Datos Azure)
Location: Mexico (Mexico City, Guadalajara, Monterrey) - Hybrid as per Infosys Mexico policy (CDT/EDT time)

Role Overview
As a Lead Azure Data Engineer, you will drive the architecture, design, and optimization of scalable data platforms and pipelines on Azure, while providing technical leadership and guidance to engineering teams. You will apply advanced expertise in SQL, Python, and Spark to build efficient ETL/ELT solutions, lead data modeling and performance tuning efforts, and ensure seamless integration with diverse data sources and BI tools. Additionally, you will establish and enforce data governance, security, and compliance standards, collaborate with stakeholders to translate business needs into robust solutions, and mentor team members to ensure high-quality delivery and alignment with enterprise data strategy.

• Monitor and respond to alert emails regarding execution failures across all team tools-such as Databricks, Azure Data Factory, or data quality gap reports within our processes.
• Proactively respond to user questions on team Zoom channels, capture issues in our processes, and implement necessary fixes.
• Work extensively with Azure Cloud Services, Azure Data Factory, Databricks, Python, and Spark, snowflake including handling user requested break-ins such as issue investigation, missing data analysis and remediation of jobs or pipelines that did not run according to their pre-configured schedules.

• Bachelor's degree or foreign equivalent in Computer Science or related field.
• 8+ years of IT experience , including pipeline design, support and development (Batch and Streaming) using Azure cloud services and Snowflake.
• Excellent assertive communication with users and stakeholders in English.
• Understanding of Agile methodologies.

• Proficiency in Python: Advanced/expert-level proven experience in Python and Spark.
• Strong understanding of ETL/ELT processes: Proven experience designing and maintaining ETL processes in Databricks and Azure Data Factory, including connectivity with third party systems/APIs, Event Hubs, Snowflake and other potential data sources.
• Experience with Azure Cloud Services: Demonstrated knowledge of cloud platforms-specifically Azure-including storage, security, and resource optimization.

• Experience working with Git-based version control (e.g., GitHub, GitLab, Bitbucket) and familiarity with branching strategies, pull requests, and code review workflows.
• Focus on system maintenance: Strong emphasis on proactive detection and fast reactive maintenance of running jobs and pipelines.

• Ability to work under tight timelines and manage complex requirements.
• Flexible to work during CDT/EDT time zones and meet for hand-over activities to India team if needed.
• Self-motivated, proactive, and a strong team player.