Data Engineer (Azure) - Remote, Latin America

Responsibilities

• ETL Data Engineering: Develop and maintain ETL data engineering processes using Python (PySpark) within Azure Synapse Analytics Notebooks, and/or Azure Synapse Analytics Pipelines, to ensure efficient data extractions, transformation, and loading.
• Data Warehousing: Apply your expertise in data warehousing, understanding star schemas, facts, and dimensions, to design and build effective data storage structures in a Massively Parallel Processing (MPP) SWL Pool.
• Data Source Expertise: Extract data from various sources, including REST APIs, SWL database tables, and CSV files.
• Azure Synapse Analytics Expertise: Utilize your deep knowledge of Azure Synapse Analytics to design and optimize data notebooks/pipelines for scalability and performance.
• Data Fabric Concepts: Contribute to the implementation and understanding of other Data Fabric concepts, such as data lakes, lakehouses, delta lakes, and data cataloging, to enhance data management capabilities.
• Data Modeling: Collaborate with data architects to create data models and schemas that align with business requirements.
• Data Quality: Implement data quality checks and validation processes to maintain data accuracy and consistency.
• Performance Tuning: Identify and resolve performance bottlenecks and optimize ETL data notebooks/pipelines to meet SLAs.
• Monitoring and Troubleshooting: Monitoring ETL jobs, diagnose issues, and implement solutions to ensure data pipeline reliability.
• Documentation: Maintain comprehensive documentation of ETL data engineering processes, data flows, and data transformations.
• Collaboration: Work closely with cross-functional teams to understand data requirements and provide support for data-related initiatives.
• Security and Compliance: Ensure data security and compliance with data governance and privacy standards.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, or a related field; or equivalent work experience, with certifications related to data engineering or data science (e.g. Azure Data Engineer) being a plus.
• Proven experience in ETL data engineering with significant expertise in using Python (PySpark) to perform data extraction, transformation, and loading from REST APIs, SQL database tables, and CSV files.
• Proficiency in using Azure Synapse Analytics resources including Notebooks, Pipelines, Linked Services, and Azure Key Vault.
• Demonstrated ability to write complex SQL queries, optimize query performance, and work with both SparkSQL and MS SQL to effectively extract, transform, and load data.
• Knowledge of data integration best practices and tools.
• Experience with version control systems, such as Git (Azure DevOps).
• Strong problem-solving and analytical skills, with a keen attention to detail.
• Excellent communication skills, both verbal and written, with the ability to work collaboratively in a team environment with shifting priorities.
• Familiarity with big data technologies, machine learning, and data analysis preferred.
• Experience with data visualization tools (e.g. Power BI, Tableau) and Agile Methodologies a plus.