Experience Level: 8 10 Years
Location: [Latam/Remote]
Role OverviewWe are seeking a high-caliber Senior Data Engineer with a deep specialization in both modern cloud data platforms and traditional BI stacks. You will be responsible for designing, developing, and deploying complex data pipelines and multi-dimensional cubes that power enterprise-level decision-making. The ideal candidate has a "full-stack" data background-bridging the gap between heavy-duty ETL processing and front-end visualization.
Key ResponsibilitiesData Orchestration & ETL: Design and maintain scalable data pipelines using Azure Data Factory (ADF) and Databricks . Migrate or optimize legacy workflows from DataStage to modern cloud environments.
Modeling & Architecture: Build and manage high-performance SSAS Tabular and Multi-dimensional cubes , ensuring data integrity and optimal query performance for end-users.
Transformation: Write complex, optimized SQL and Spark-based transformations to handle large-scale datasets within a Lakehouse architecture.
BI Delivery: Develop and maintain sophisticated dashboards and self-service reporting environments using Tableau, Cognos, and ThoughtSpot .
Deployment & Ops: Lead the deployment of data solutions, ensuring best practices in version control, security, and automated testing are followed.
8 10 years of total software development experience with a focus on data-centric applications.
7+ years of Hands-on Expertise in the following:
Advanced SQL: Expert-level querying, performance tuning, and stored procedure development.
ETL/ELT Frameworks: Extensive experience with DataStage and ADF for complex data movement.
Big Data: Proven experience using Databricks (PySpark/Scala) for data processing.
OLAP Cubes: Deep knowledge of SSAS (SQL Server Analysis Services) for building complex data models.
BI Visualization: Proficiency across multiple platforms including Tableau, Cognos, and ThoughtSpot .
Cloud Proficiency: Solid understanding of cloud infrastructure (preferably Azure) as it relates to data storage and compute.
Experience with Python for data automation beyond basic ETL.
Familiarity with DAX or MDX for advanced SSAS calculations.
Understanding of Data Governance and Master Data Management (MDM) principles
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