Overview We are seeking a highly experienced Databricks Data Engineer to design, develop, and optimize large-scale data platforms supporting critical business functions within a financial services environment. The successful candidate will play a key role in building and enhancing a modern data ecosystem based on Databricks, leveraging a Medallion Architecture (Bronze, Silver, Gold, Publish) to deliver trusted, scalable, and business-ready data products. This role requires deep expertise in Big Data technologies, including Hadoop, Hive, Spark, Databricks, and modern data engineering practices, with a strong focus on data modeling, pipeline development, performance optimization, and data quality. Main Responsibilities
• Design, build, and maintain scalable data pipelines using Databricks and Apache Spark.
• Develop and support Medallion Architecture data layers (Bronze, Silver, Gold, Publish).
• Implement incremental data ingestion, transformation, and reconciliation processes.
• Develop reusable frameworks and best practices for data engineering and pipeline orchestration.
• Design and optimize large-scale ETL/ELT workflows for structured and semi-structured data.
• Integrate data from multiple enterprise source systems while ensuring data governance and security standards.
• Implement data quality controls, monitoring, validation, and operational alerting.
• Collaborate with architects, business stakeholders,



analysts, and engineering teams to define scalable data solutions.
• Troubleshoot and optimize Spark workloads for performance, scalability, and cost efficiency.
• Support enterprise data initiatives within customer, application, account, and other business domains. Key Requirements
• 7+ years of experience in Data Engineering, Big Data, or related fields.
• 5+ Years of experience fully focused in Databricks (Must)
• Fluent conversational English required, with strong verbal and written communication skills. (Must
- B2 onwards)
• Extensive experience with Hadoop ecosystem technologies, including: Hadoop / Hive / Spark
• Proven experience building enterprise-scale ETL/ELT pipelines.
• Strong understanding of Data Warehouse concepts, dimensional modeling, and SCD Type 2.
• Experience working with Medallion Architecture and modern Lakehouse platforms.
• Advanced SQL development and performance tuning skills.
• Experience handling large-volume datasets in distributed computing environments.
• Knowledge of data quality, reconciliation, monitoring, and operational support practices.
• Experience with data security, sensitive data handling, and data tokenization.
• Strong problem-solving and analytical skills.
• Ability to work effectively in Agile delivery environments.

📌 Databricks Data Engineer (Colombia)
🏢 EXL
📍 Colombia