Sobre el puesto

Company Description We are looking for a Senior Data Engineer to join our Data Engineering Team and take ownership of high-impact, greenfield data initiatives. You will work on building modern cloud-native data platforms, migrating on-premises legacy systems to the cloud, and laying the architectural foundation for AI-ready data infrastructure. In this role, you will collaborate closely with Machine Learning, Data Science, and Product teams, serving as a key technical contributor and thought leader. You will also drive R&D efforts around agentic AI architectures, event-driven systems, and LLM-ready data pipelines – turning architectural concepts into production-grade solutions. Job Description - Design and build scalable cloud-native data platforms from greenfield to production - Design and implement near-real-time ingestion pipelines using event-driven patterns - Define and enforce data platform standards including Data Lake and Lakehouse principles, medallion architecture, and data contracts - Refactor, optimize, and modernize Spark and PySpark scripts for performance and maintainability - Introduce best practices for code quality, testing, and CI/CD across data pipelines - Drive adoption of AI tooling and agentic workflows within the Data Engineering team - Ensure data quality, observability, scalability, and reliability across all platforms and pipelines - Design and deliver self-service tooling and microservices that simplify platform usage - Collaborate with cross-functional stakeholders including Product, Machine Learning, and Data Science teams - Contribute to architecture decisions and technical R&D initiatives Qualifications - 5+ years of professional experience in Data Engineering - Strong Python and SQL development skills - Hands-on experience with Apache Spark and PySpark including query optimization and performance tuning - Experience working with Databricks or Snowflake - Practical experience with at least one major cloud provider such as Azure, AWS, or GCP - Experience with stream processing technologies including Kafka or Spark Structured Streaming - Strong understanding of ETL/ELT patterns, data modelling, and data warehousing concepts - Experience with orchestration tools such as Apache Airflow or Azure Data Factory - Knowledge of Infrastructure as Code tools including Terraform - Understanding of production-grade systems including observability, scalability, reliability, and performance - Ability to independently lead technical initiatives from concept to delivery - Strong communication and collaboration skills - Upper-Intermediate or higher English level WILL BE A PLUS - Familiarity with RAG pipeline design and LLM integration patterns - Knowledge of data governance frameworks and tools such as Unity Catalog or Apache Atlas - Experience with dbt for data transformation and modelling - Familiarity with MLflow, Feature Stores, or ML platform integrations Additional Information PERSONAL PROFILE - Proactive and self-driven mindset - Strong analytical and architectural thinking - Ability to work independently and take ownership of technical decisions - Passion for innovation and modern engineering practices - Knowledge-sharing and team-oriented approach - Strong problem-solving skills