YOUR MISSION

We are looking for a world-class Senior Data Engineer to help shape and scale our data platform, powering insights and decision-making across our suite of SaaS digital advertising products. You’ll play a key role in designing and building robust, scalable data pipelines and services that fuel analytics, machine learning, and customer-facing features.
You’ll collaborate closely with Product Managers and Engineers to ensure our data systems are performant, reliable, and aligned with business goals. You’ll contribute hands-on to critical projects, lead technical discussions, conduct code reviews, and guide others in best practices for data engineering.
To thrive in this role, you should bring strong expertise with building and managing a modern data stack – particularly familiarity with Lakehouse architecture and cloud-based data platforms.
Experience with AWS cloud platform and technologies like dbt, Apache Spark, Apache Kafka/Amazon Kinesis, and Apache Airflow/Dagster are highly valuable. You’re passionate about clean, efficient data architecture and have a proven track record of mentoring others and improving engineering culture.
An accomplished Senior Data Engineer at Factor Eleven is someone who consistently raises the bar – delivering high-quality solutions, strengthening team collaboration, and leaving lasting improvements in system design, data reliability, and team growth.

• Design, build, and maintain data pipelines, architectures, and platforms, ensuring scalability, reliability, and efficiency.
• Develop and implement ETL/ELT processes to move and transform data for analysis, ensuring data accuracy, completeness, and consistency through quality checks and governance frameworks.
• Mentor and support the growth of fellow data engineers by sharing best practices and encouraging a culture of learning.
• Work closely with peers across engineering, product, and business teams to understand requirements to unlock business insights that drive business value.
• Consistently deliver high-impact data solutions – owning timelines, sharing updates, and driving end-to-end project execution.
• Maintain and promote best practices for data engineering, testing, and documentation by actively engaging in technical reviews and design discussions.
• Stay informed about industry trends and advancements in the data ecosystem, including cloud services like AWS, big data processing, and real-time analytics.
• Help scope work, estimate complexity, and break down tasks for yourself and the team to ensure on-time and high-quality delivery.