Argentina onlyPosition: Data Engineer
Role Overview:
- Collaborate with Architects to develop high-quality data pipelines for research, operations, and public web applications.
- Support current and future reporting and analytics solutions.
- Apply expertise in data architecture, data engineering, and reporting.
Responsibilities:
- Architect, design, and build scalable, robust, and efficient data pipelines using Azure Data Factory and other cloud-native tools.
- Establish best practices for data ingestion, transformation, storage, and access, optimizing for performance and cost-efficiency.
- Design and implement complex data models, schemas, and partitioning strategies for analytical and operational workloads.
- Champion modern data modeling strategies such as medallion architecture.
- Define and enforce frameworks for data quality, lineage, and observability.
- Enhance data platform infrastructure including CI/CD, monitoring, cost optimization, and failover strategies.
- Optimize performance of SQL Server and PostgreSQL databases and cloud services by identifying and resolving bottlenecks.
- Collaborate with product, analytics, and business teams to translate business goals into data architecture and pipeline solutions.
- Serve as the technical subject matter expert for data platforms and initiatives.
- Identify automation opportunities, streamline operations, and promote data democratization.
- Maintain comprehensive technical documentation, architecture diagrams, and operational playbooks.
- Ensure architectural consistency and enforce data security across all services and platforms.
- Work with Architects to model analytical data models, data warehouses, pipelines, and ETL processes.
Skills & Qualifications:
- Bachelor’s degree in Computer Science, Information Systems, Information Technology, or equivalent experience.
- 8+ years of hands-on experience in data engineering or data platform development with a record of delivering production-grade solutions.
- Expertise in Azure Data Factory, SQL Server, and PostgreSQL for data ingestion, transformation, and storage.
- Strong knowledge of data warehousing principles, dimensional modeling, and scalable ETL/ELT pipeline development.
- Experience with cloud services, preferably Azure, and data security protocols.
- Proficiency in Python and/or Scala focused on building maintainable and testable data solutions.
- Excellent problem-solving skills and attention to detail.
- Proven leadership ability and experience delivering quality data solutions.
- Strong communication and collaboration skills.
- Familiarity with machine learning methodologies and data science models.
- Azure or other cloud services certifications are a plus.
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