Data Engineer (Azure)- Remote, Latin America

Requisitos e responsabilidades

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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.

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