Senior Data Engineer

• work in an agile team to design, develop, and implement data integration services that connect diverse data sources including event tracking platforms (GA4, Segment), databases, APIs, and third-party systems
• build and maintain robust data pipelines using Apache Airflow, dbt, and Spark to orchestrate complex workflows and transform raw data into analytics-ready datasets in Snowflake
• develop Python-based integration services and APIs that enable seamless data flow between various data technologies and downstream applications
• collaborate actively with data analysts, analytics engineers, and platform teams to understand requirements, troubleshoot data issues, and optimize pipeline performance
• participate in code reviews, sprint planning, and retrospectives to ensure high-quality, production-ready code by end of each sprint
• contribute to the continuous improvement of data platform infrastructure, development practices, and deployment processes in accordance with CI/CD best practices

• successfully implemented and released data integration services or APIs using modern Python frameworks in the past 4 years
• successfully designed data models and schemas for analytics or data warehousing solutions
• strong analysis and problem solving skills
• strong knowledge of Python programming language and data engineering
• deep understanding of good programming practices, design patterns, and software architecture principles
• ability to work as part of a team by contributing to product backlog reviews and solution design and implementation
• be disciplined in implementing software in a timely manner while ensuring product quality isn't compromised
• formal training in software engineering, computer science, computer engineering, or data engineering
• have working knowledge with Apache Airflow or a similar technology for workflow orchestration
• have working knowledge with dbt (data build tool) for analytics transformation workflows
• experience with cloud data warehouses (Snowflake preferred) and distributed computing frameworks (Apache Spark)
• experience integrating with event tracking platforms (e.g., Google Analytics 4, Segment, Amplitude) and third-party data sources
• understanding of data modeling concepts including dimensional modeling, slowly changing dimensions, and incremental loading patterns
• have working knowledge with containerization (Docker/Kubernetes) and CI/CD pipelines
• successfully implemented data APIs and integration services that seamlessly connect various data technologies
• English level: B2 (Upper-intermediate)

experience with AI tools