Lead the creation and development of a new Market Data engineering team, shaping both the people and systems that power data acquisition and processing. You'll establish strong engineering practices while designing scalable, maintainable data platforms that serve as the backbone of data-driven decision-making.
What You'll Do
Build and guide a team of backend and data engineers, fostering a culture of ownership, accountability, and continuous improvement. Design and implement robust data pipelines in cloud environments, transforming fragmented workflows into structured, observable systems. Drive architectural standards across data modeling, ETL/ELT processes, and system scalability.
Stay actively involved in technical discussions, code reviews, and occasional development to maintain hands-on expertise. Mentor engineers through complex design challenges and career growth, conducting regular 1:1s and performance feedback sessions. Collaborate with engineering leadership to align data strategy with broader technical goals and promote consistency across teams.
Requirements
- Proven experience leading technical teams or serving in a team lead capacity
- Minimum of four years of production-level Python development
- Hands-on experience building and maintaining ETL/ELT pipelines in cloud data warehouses such as Snowflake, BigQuery, Databricks, or Redshift
- Strong background in data modeling, including analytics-ready schema design and performance optimization
- Experience with workflow orchestration tools like Dagster, Airflow, or similar
- Deep understanding of system architecture with emphasis on long-term maintainability and scalability
- Ability to operate effectively in ambiguous environments and drive clarity through structured thinking
- Fluent English communication and based in the European time zone (UTC+0 to UTC+2)
- Strong commitment to engineering excellence, including testing, documentation, and observability
- Collaborative mindset with a focus on trust-building across distributed teams
Preferred Qualifications
- Experience managing performance reviews and career development conversations
- Background in building or overhauling data platforms from the ground up
- Experience scaling engineering teams during high-growth phases
- Practical knowledge of dbt for data transformation, testing, and documentation
- Familiarity with Django or FastAPI frameworks
- Experience with monitoring and observability tools such as Datadog or Sentry
- Working knowledge of distributed task queues like Celery and RabbitMQ
- Understanding of cost-efficient design patterns in data-intensive applications
Benefits
- Fully remote work with flexibility to operate within European time zones
- Option to work from co-working spaces or offices in Mannheim, Berlin, or Sydney
- Annual global team meetups combining strategy and social connection
- Regular local team gatherings to strengthen collaboration
- Opportunities for personal and professional growth
- Up to three additional days off per year dedicated to learning and development
- Five extra weeks of vacation after five years of employment
- Paid day off on your birthday
- Flexible hours to support work-life balance
- Access to Headspace for mindfulness and mental wellbeing
- Subscription to BetterHelp for confidential online therapy and counseling
