We need a Sr Data Engineer for a long term remote opportunity.

Responsibilities

• Build scalable production-grade data pipelines and real-time data streams
• Writing and designing highly scalable, highly available, cloud-ready applications
• Be well-versed in ETL design, implementation, and maintenance
• Collaborate with Machine Learning, Data Science, Design, Software Engineering, and Business teams to triage data or ETL issues that are causing anomalies
• Analyze and find issues in the data and work to prioritize and find solutions
• Build out tests and health checks to ensure the quality level of code and data
• Monitor, analyze, and understand the data flowing through a system by adding the necessary visualizations and dashboards
• Provide updates, inform blockers and offer guidance to clients
• Leading technical projects through architecture, design, and implementation phases

Requirements

• [MUST HAVE] Advanced level of Python and SQL
• [MUST HAVE] Prior working experience in one of the three Cloud Providers (AWS, GCP, or Azure) to deliver data-centric product experiences.
• [MUST HAVE] Advanced Conversational English Skills
• 3+ years of experience in related roles
• Fundamental understanding and work experience of in-memory and disk-based databases, relational and nonrelational databases, full-text search engines, database design, development, and maintenance.
• Experience with data warehousing and multidimensional data models. (Columnar data modeling)
• Working knowledge in Data Lake, Data warehouse, and massive parallel processing.
• Working knowledge in a few topics: IAM, Federated Authentication, SSO, SAML, Encryption, Security, APIs, Disaster Recovery, and Backup.
• Strong problem-solving ability and ability to work through ambiguity and incomplete specifications
• Dedication to code quality, testing, design processes, automation, and operational excellence
• Strong ability in distributed systems for processing large-scale data processing
• Good communication skills. You should feel comfortable having in-depth technical discussions
• (Bonus) Spark and Pandas experience
• (Bonus) Infrastructure as Code and CI/CD Pipelines