Senior Data Engineer

Summary

Join Factor Eleven as a Senior Data Engineer to design, build, and maintain scalable data pipelines and platforms for our SaaS digital advertising products. Collaborate with Product Managers and Engineers to ensure data system performance and alignment with business goals. Mentor fellow data engineers, lead technical discussions, and contribute to critical projects. Leverage your expertise in building modern data stacks, particularly Lakehouse architecture and cloud-based platforms. This role requires strong AWS, Python, and SQL skills, along with experience in tools like dbt, Apache Spark, and Kafka/Kinesis. You will consistently deliver high-impact data solutions and promote best practices for data engineering.

Requirements

• 5+ years of professional experience in data engineering, with a deep focus on building and scaling data platforms and infrastructure
• Excellent understanding of different data modelling techniques and their trade-offs
• You have experience building and maintaining a modern data stack from scratch
• Advanced proficiency in Python and SQL, with experience using tools Apache Spark, Apache Kafka/Amazon Kinesis, Apache Airflow/Dagster and dbt
• You build resilient, well-tested data systems with a focus on performance, security, and maintainability
• You’re an excellent communicator – capable of explaining complex technical topics to both technical and non-technical stakeholders, and you lead with empathy during difficult conversations
• Solid foundation in computer science, with expertise in data structures, distributed systems, data modeling, and big data processing frameworks
• Proven track record of influencing strategic decisions through architectural leadership and cross-functional collaboration
• Experience organizing technical workshops or sessions, nurturing a growth mindset and a culture of engineering excellence
• Deep understanding of scalable data system design, including data lakes, data warehouses (e.g. Snowflake, BigQuery), and real-time streaming systems (e.g Kafka, Kinesis)
• Strong advocate of automated testing and CI/CD for data pipelines and infrastructure
• Highly collaborative with exceptional problem-solving skills and the ability to mentor others in a supportive and respectful way
• Excellent organizational and project management skills – you can juggle priorities and keep projects on track
• Passion for mentoring and knowledge sharing – you thrive in helping others grow and succeed

Responsibilities

• 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

Benefits

• Transparent, above-market salaries
• 100% remote within Europe
• Flexible work-hours and part-time models
• Be part of a fast-growing, highly-skilled team
• In person department and company events
• Home office, co-working space and work-together allowance
• Personal and professional development courses from Udemy
• Case by case relocation and visa support