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Senior Data Engineer

Posted 8 days agoViewed

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💎 Seniority level: Senior, 7+ years

🔍 Industry: Fintech

⏳ Experience: 7+ years

Requirements:
  • 7+ years of experience with ETL, SQL, PowerBI, Tableau, or similar technologies
  • Strong understanding of data modeling, database design, and SQL
  • Experience working with Apache Kafka or MSK solution
  • Extensive experience delivering solutions on Snowflake or other cloud-based data warehouses, and generally an understanding of data warehousing technologies and event-driven architectures
  • Proficiency in Python/R and familiarity with modern data engineering practices
  • Strong analytical and problem-solving skills with a focus on delivering high-quality solutions
  • Experience with machine learning (ML) and building natural language interfaces for business data
  • Proven track record in a fast-paced Agile development environment
  • Ability to work autonomously while effectively engaging with multiple business teams and stakeholders
Responsibilities:
  • Design, develop, and maintain scalable data pipelines for ingesting, processing, and transforming large volumes of data from various sources
  • Implement data ingestion frameworks to efficiently collect data from internal and external sources
  • Optimize data pipelines for performance, reliability, and scalability
  • Develop and deliver scalable, unit-tested data assets and products that empower analysts and drive business workflows
  • Evaluate and continuously improve existing data products and solutions for performance, scalability and security
  • Experience in data quality management, including software implementation for data correction, reconciliation, and validation of data workflows to ensure accuracy and integrity in the data warehouse
  • Collaborate with engineers, data scientists, and product managers to analyze edge cases and plan for architectural scalability
  • Lead the deployment and maintenance of multiple data solutions such as business dashboards and machine learning models
  • Champion best practices in data development, design, and architecture
  • Conduct comprehensive code reviews, providing mentorship and meaningful feedback to junior team members
  • Collaborate with other team members to create and maintain process documentation, data flows, and ETL diagrams for both new and existing data pipelines and processes
  • Monitor data pipelines for performance, reliability, and security issues
  • Implement logging, monitoring, and alerting systems to detect and respond to data-related issues proactively
  • Drive the team's Agile process, ensuring high standards of productivity and collaboration
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