Senior Data Engineer

This is a fully remote position, open to applicants in Latin America.

📋 Description

• Design, construct, and sustain high-performance batch and real-time streaming data pipeline architectures.

• Ingest, process, and reliably deliver extensive, complex datasets.

• Automate manual workflows and enhance query execution efficiency.

• Re-engineer cloud infrastructure to boost data freshness, scalability, and resilience against failures.

• Develop production-grade ETL/ELT pipelines utilizing Python, SQL, Azure, and/or GCP.

• Extract and consolidate data from various distributed sources.

• Create, test, and maintain data tools, data marts, and feature stores.

• Empower analytics engineers and data scientists to implement efficient models and business intelligence solutions.

• Collaborate with cross-functional stakeholders across North America.

• Lead root cause analysis to address pipeline bottlenecks.

• Manage dependencies and ensure robust data governance across different environments.

⛳️ Requirements

• 4+ years of professional experience in data engineering.

• Demonstrated expertise in data modeling, metadata management, and workload orchestration.

• Advanced skills in Python and complex SQL.

• Practical production experience with Databricks.

• Hands-on experience with Apache Spark.

• Familiarity with Azure Data Factory, Azure Synapse, or Google BigQuery.

• Experience in architecting both stream-based and batch-oriented data pipelines.

• Ability to manage semi-structured and unstructured data at scale.

• Advanced English proficiency (B2+/C1).

• Outstanding written and verbal communication skills.

• Comfortable leading technical discussions with U.S.-based engineering teams during East or West Coast business hours.

🏝️ Benefits

• USA Contractor / 100% Remote.

• Competitive Pay (USD).

• Holidays Off & Paid Time Off.

• Health insurance assistance program.

• Opportunity to collaborate with high-growth U.S.-based companies and innovative tech stacks.

• Access to Agentic AI tools and training.

• Coursera Enterprise.

• Studio practice laboratories.

• Comprehensive onboarding experience.

• Open leadership communication.

• Community recognition.

• Emphasis on psychological safety.

• Ongoing multi-project pipeline.

• Direct interaction with U.S. client teams and their roadmaps.