Sr. Data Analytics Engineer

Overview

Sr. Data Engineer responsible for designing, developing, and maintaining data platforms, leading large cross-functional technical initiatives, and mentoring junior engineers.

What you'll do

• Design and implement scalable, efficient, and reliable data architectures that support business and analytical needs.
• Build and maintain data pipelines, ETL processes, and integration solutions for large volumes of structured and unstructured data.
• Optimize data pipelines, databases, data warehouses, and data lakes for performance, reliability, scalability, and security.
• Partner with stakeholders to understand data requirements, develop domain expertise, and translate business needs into effective data models and solutions.
• Establish and improve data quality standards, validation rules, documentation, and governance practices.
• Implement monitoring and observability practices to identify bottlenecks, improve performance, and strengthen platform reliability.
• Provide technical leadership on architecture, scalability, reliability, monitoring, integration, and extensibility.
• Lead and contribute to code reviews, helping maintain high standards for code quality, performance, and maintainability.
• Mentor junior engineers and support a culture of continuous learning and technical excellence.
• Take ownership of production issues, including troubleshooting, root-cause analysis, escalation, and long-term resolution.
• Independently lead multiple features and projects, coordinate work across engineers, and keep stakeholders informed of progress, risks, and dependencies.
• Help evolve engineering tools, platforms, and practices and encourage adoption of better ways of working.
• Look for practical ways to use AI tools to improve engineering productivity, analysis, documentation, and problem-solving.

What you'll need

• 8+ years of experience in data engineering, with strong experience in data architecture, ETL, and database management.
• Strong programming skills in Python or PySpark, plus experience with Java or Scala.
• Experience building complex end-to-end data pipelines and data integration solutions.
• Strong knowledge of SQL and experience with relational and NoSQL database technologies.
• Experience with big data technologies such as Spark, Kafka, Hadoop, or similar platforms.
• Experience with orchestration and scheduling tools such as Airflow, Databricks, Jenkins, or similar technologies.
• Experience designing and operating scalable, reliable, and secure data systems.
• Familiarity with cloud platforms such as AWS, Azure, or GCP and associated data services.
• Experience working in Agile environments such as Scrum, Lean, or Kanban.
• Strong problem-solving and decision-making skills.
• Experience mentoring junior engineers and contributing to technical leadership within a team.
• Strong written and verbal communication skills with the ability to work effectively across technical and non-technical teams.

Nice to have

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Databricks experience or certification.
• Experience with AWS Redshift, S3, Azure SQL Data Warehouse, or comparable cloud data services.
• Experience implementing data governance, data quality, or observability frameworks.
• Experience leading cross-functional or multi-month engineering initiatives.
• Experience using AI-assisted engineering tools to improve development, troubleshooting, documentation, or productivity.

Details

• Remote position based in Mexico.