Sr. Data Engineer

Responsibilities

• Architect, build, test, deploy, and maintain scalable, automated ETL/ELT pipelines using Python, dbt, and orchestration tools such as Prefect and Airflow
• Administer and optimize cloud-based data warehouse and lake platforms, including Snowflake, AWS (S3, Redshift), and Google Cloud, integrating new sources and tuning for performance and cost
• Orchestrate data workflows with custom scheduling, alerting, dependency management, monitoring, and error resolution
• Design and maintain secure external data flows through SFTP, Files.com, and APIs, with a focus on reliability and compliance
• Automate manual reporting and operational tasks, building robust, reusable pipeline components that reduce operational overhead
• Partner with backend product engineers to optimize production database schemas with analytics use cases in mind
• Strengthen data quality, lineage, governance, and documentation practices across key data domains
• Mentor teammates and reinforce best practices in version control, code review, and structured workflow management
• In your first 12–18 months, you will have
• Taken end-to-end ownership of core pipelines and integrations, with measurable improvements in reliability, data recency, and cost efficiency

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