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Key Responsibilities
Design, develop, and support data replication and integration solutions using HVR
Design, build, and maintain scalable data pipelines using Databricks (Spark, Delta Lake)
Develop and optimize ETL/ELT processes for structured and unstructured data
Work with large datasets to ensure data quality, integrity, and performance optimization
Implement data models and transformations for analytics and reporting
Collaborate with data scientists and analysts to enable advanced analytics and ML workloads
Integrate data from multiple sources including databases, APIs,



and streaming systems
Optimize Spark jobs for performance tuning and cost efficiency
Implement data governance, security, and access controls
Monitor and troubleshoot data pipelines and production issues
Support CI/CD pipelines and DevOps best practices for data engineering workflows
Support data migration and modernization initiatives.
Ensure data quality, governance, security, and compliance standards.
Create operational documentation, runbooks, and support procedures.
Participate in production support, issue resolution, and performance tuning activities.

Technical Skills
Hands-on experience with data engineering or big data development
Strong knowledge of:
SQL / Oracle / SQL Server
Java / JavaScript (preferred)
Web-based applications and APIs (REST/SOAP)
Strong experience with:
Databricks Platform
Apache Spark (PySpark/Scala)
SQL & Python
Experience with Delta Lake and data lake architecture
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📌 Senior Data Engineer (Colombia)
🏢 Capgemini Engineering
📍 Colombia