Azure Data Engineer - Remote, Latin America
Remote · Barranquilla, Atlántico, Colombia
Job Summary
As an ETL Data Engineer, develop and maintain ETL data engineering processes using Python (PySpark) within Azure Synapse Analytics Notebooks and/or Pipelines to ensure efficient data extraction, transformation, and loading. Design and build data warehouses with star schemas within an MPP SWL Pool; extract data from REST APIs, SQL tables, and CSV files; leverage Azure Synapse Analytics to optimize notebooks and pipelines for scalability and performance. Contribute to data fabric concepts (data lakes, lakehouses, delta lakes, data cataloging), collaborate with data scientists and analysts, implement data quality checks, monitor ETL jobs, troubleshoot, and document data flows and transformations. Possess strong collaboration skills, knowledge of data governance and security practices, and familiarity with Power BI/Tableau for data visualization; experience with Git/Azure DevOps and Agile methodologies is a plus.
Required Qualifications
- Bachelor’s degree in Computer Science, Information Technology, or a related field; or equivalent work experience
- Proven experience in ETL data engineering with Python (PySpark) to extract, transform, and load from REST APIs, SQL database tables, and CSV files
- Proficiency with Azure Synapse Analytics resources including Notebooks, Pipelines, Linked Services, and Azure Key Vault
- Strong SQL skills (SparkSQL and MS SQL) and experience with data integration best practices
- Experience with version control systems such as Git (Azure DevOps)
- Excellent communication and teamwork skills; ability to work in a collaborative environment
- Familiarity with big data technologies, machine learning, and data visualization tools (Power BI, Tableau) should be a plus
Desired Qualifications
- Bachelor’s degree in Computer Science, Information Technology, or a related field; certifications related to data engineering or data science (e.g. Azure Data Engineer) being a plus
- Proven experience in ETL data engineering with Python (PySpark) for data extraction, transformation, and loading from REST APIs, SQL database tables, and CSV files
- Proficiency with Azure Synapse Analytics (Notebooks, Pipelines, Linked Services, Azure Key Vault)
- Strong SQL skills (SparkSQL and MS SQL), data warehousing concepts, and data modeling
- Experience with Git/Azure DevOps, data visualization tools (Power BI, Tableau), and Agile methodologies
- Knowledge of data integration best practices, data quality checks, performance tuning, and data governance concepts
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