Data Engineer at OP3N

Job Description

Key Responsibilities

• Conduct a comprehensive audit of the existing data infrastructure and availability within Cloud Firestore to identify inefficiencies and opportunities for optimization.
• Specify and implement a new data warehouse solution, such as Snowflake, to replace or enhance the current infrastructure, ensuring scalability, performance, and cost-effectiveness.
• Collaborate with the Product team to develop a scalable data infrastructure and analytics framework that can handle increasing user data volumes and evolving business needs.
• Partner with engineering teams to design and deploy data pipelines that enable efficient data ingestion, transformation, and querying across multiple sources.
• Continuously monitor and improve data quality, workflow reliability, and system scalability by exploring emerging technologies and refining existing processes.
• Provide performance reports and insights to stakeholders, demonstrating the capabilities and impact of data infrastructure improvements.
• Own the data lifecycle for new products and features, including defining data sources, designing warehouse architectures, and establishing reporting mechanisms.
• Ensure data systems are aligned with organizational goals by balancing technical requirements with business priorities.
• Lead the evaluation of data governance frameworks and ensure compliance with regulatory standards and internal policies.
• Develop and maintain documentation for data systems, including architecture diagrams, process flows, and technical specifications.

Job Requirements

• Proven experience in designing and managing cloud-based data infrastructure, with a strong background in Cloud Firestore and Snowflake technologies.
• Advanced knowledge of data warehousing concepts, ETL processes, and data pipeline architecture to support scalable analytics solutions.
• Ability to collaborate effectively with Product and Engineering teams to translate business requirements into technical specifications.
• Strong analytical skills to evaluate data systems, identify bottlenecks, and propose data-driven improvements.
• Experience with data quality assurance, workflow automation, and performance optimization techniques.
• Excellent communication skills to convey technical insights to non-technical stakeholders and document processes clearly.
• Proficiency in SQL, cloud computing platforms, and data visualization tools to support data analysis and reporting.
• Ability to manage multiple projects simultaneously while maintaining attention to detail and meeting deadlines.
• Experience with agile methodologies and a track record of delivering scalable data solutions in fast-paced environments.
• Knowledge of data governance principles and security best practices to ensure compliance and data integrity.
• Strong problem-solving abilities and a proactive approach to identifying and resolving technical challenges in data systems.
• Experience with cloud-native technologies and containerization tools (e.g., Docker, Kubernetes) for deploying and managing data infrastructure.
• Ability to work independently and take ownership of complex data projects from conceptualization to deployment.
• Excellent time management skills and the capacity to prioritize tasks effectively in a dynamic work environment.
• Proficiency in scripting languages (e.g., Python, Bash) for automating data processing tasks and system maintenance.