- We are seeking a skilled Databricks Engineer with strong experience in Azure Databricks and Python (PySpark) to design, build, and optimize scalable data processing pipelines.
- The idóneo candidate will work closely with data engineers, analysts, and stakeholders to deliver high-performance data solutions on the Azure cloud platform.

Key Responsibilities
- Design, build, and maintain data pipelines and ETL processes using Databricks and Apache Spark.
- Optimize data workflows for performance, scalability, and cost efficiency.
- Implement data Lakehouse architecture and manage data ingestion from multiple sources.
- Collaborate with data scientists and analysts to enable advanced analytics and machine learning workloads.
- Ensure data quality, governance, and security across all data assets.
- Monitor and troubleshoot Databricks clusters, jobs, and workflows.
- Integrate Databricks with cloud services (AWS, Azure, or GCP) and other enterprise systems.
- Document processes, standards,



and best practices for data engineering.

Required Skills & Qualifications
- Bachelor’s degree in Computer Science, Data Engineering, or related field.
- 3+ years of experience in data engineering or big data technologies.
- Hands-on experience with Databricks, Apache Spark, and PySpark.
- Strong knowledge of SQL, Python, and data modeling principles.
- Experience with cloud platforms (AWS, Azure, or GCP) and their data services.
- Familiarity with Delta Lake, Lakehouse architecture, and data governance.
- Understanding of CI/CD pipelines and DevOps practices for data workflows.
- Excellent problem-solving and communication skills.

Nice to Have
- Experience with Delta Lake and Lakehouse architecture.
- Knowledge of Azure Data Factory (ADF) for orchestration.
- Experience with SQL and Spark SQL.
- Azure certifications related to data engineering.

📌 Data Engineer (México)
🏢 Pyramid Consulting
📍 México