Senior Data Systems Engineer

• Drive technical implementation and testing of complex data pipeline features within the SPECTRA platform, ensuring robust end-to-end functionality and meeting project release timelines.
• Design and develop data processing pipelines using SQL and Python to handle large-scale data collection, transformation, and quality monitoring workflows.
• Build and maintain dashboards and visualization tools to provide visibility into data quality, rater performance, and platform metrics for stakeholders across multiple teams.
• Create comprehensive end-to-end tests and monitoring alerts to ensure platform reliability, data integrity, and proactive identification of issues in the data collection workflow.
• Debug and troubleshoot complex data flow issues across the SPECTRA platform, identifying root causes and implementing solutions to maintain high system availability.
• Collaborate closely with Technical Leads and engineering teams to implement backend data processing logic and ensure adherence to development standards and best practices., PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

• Experience in SQL development writing complex queries, data transformations, and working with large datasets in production environments.
• Proficient in Python with experience in data processing, automation, and pipeline development using object-oriented programming principles.
• Experience with data engineering pipelines including ETL processes, data modeling, and building scalable data processing workflows.
• Hands-on experience with data visualization and dashboard tools such as Tableau or similar platforms for creating actionable insights from large datasets.
• Strong analytical and problem-solving skills with demonstrated ability to debug complex data issues and implement effective solutions.
• Experience with data quality monitoring and automated testing frameworks to ensure data accuracy, completeness, and reliability.

Preferred

• Degree in Computer Science or related field.
• Machine Learning experience with understanding of ML model training data requirements, feature engineering, and model evaluation metrics.
• Experience building and scaling large products or systems.
• Experience with building privacy and ads-related products is a big plus.
• Experience working with human labeling and annotation systems including workflow design, quality assurance, and vendor management in data collection operations.
• Prior experience working with the company or its internal tools is a plus.

• Hourly contractor, Paid weekly via Stripe Connect.

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