Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, construct, and maintain comprehensive data pipelines, encompassing both batch and/or streaming workflows, from ingestion to transformation and delivery.

• Develop and manage reliable, scalable, and high-performance ETL/ELT workflows.

• Create efficient, production-ready SQL queries for data extraction, transformation, and analytics purposes.

• Implement and sustain data models, such as star schemas and incremental models, optimized for analytics and reporting.

• Write reusable, modular, and maintainable Python code for data transformations and pipeline logic.

• Monitor data pipelines, troubleshoot failures, and conduct root cause analysis across code, orchestration tools, data sources, and cloud services.

• Ensure data quality by employing automated schema validation, freshness checks, and row-level assertions.

• Collaborate with analysts, backend engineers, and stakeholders to establish data contracts and guarantee reliable data availability.

• Engage in the planning, estimation, and prioritization of data engineering tasks.

• Identify risks associated with performance, scalability, and data integrity while proposing mitigation strategies.

• Contribute to the ongoing enhancement of data platforms, engineering processes, and team best practices.

• Draft and maintain technical documentation for data pipelines, schemas, and data lineage.

• Clearly communicate with team members and clients, raising inquiries and concerns when requirements or priorities are ambiguous.

⛳️ Requirements

• Professional experience as a Data Engineer working with production-level data pipelines.

• Extensive experience with SQL, including query optimization, indexing, partitioning, and understanding performance trade-offs.

• Professional experience in writing Python for data transformations, adhering to good software design and modularization practices.

• Experience in designing and implementing data models for analytics and reporting purposes.

• Experience in building and managing data pipelines using cloud-based data platforms.

• Practical experience with GCP and BigQuery.

• Experience in operating data pipelines, including error handling, monitoring, troubleshooting, and data quality processes.

• Knowledge of essential data security and governance practices, encompassing access control, data masking, and PII handling.

• Capability to independently deliver simpler tasks while managing more complex challenges with appropriate guidance.

• Strong sense of ownership, responsibility, and accountability for data workflows and deliverables.

• Good organizational and time management skills, with the ability to estimate effort and meet delivery deadlines.

• Advanced English proficiency for effective collaboration with global clients and distributed teams.

• Team-oriented mindset with strong communication, collaboration, and problem-solving abilities.

🏝️ Benefits

• 100% remote work