As a Data Engineering Manager you will be be looking after the team that maintains and improves the systems used to capture the data that helps us understand how Pitch is doing as a business. You will empower not just your team, but also stakeholders across the company, and educate and guiding them on how to produce and consume the data relevant to their needs.

Curious about our engineering culture? Our CTO and co-founder Adam Renklint recently contributed to a blog post that dives deep into our technical foundation, our iterative approach to development and our philosophy on building a sustainable engineering culture that’s all about joyful work. For further reading on our team's values, check out our Engineering Principles.

What you will do

• Own the technical roadmap for Data Engineering and advocate for technical initiatives to improve efficiency, scalability, and maintainability of the codebase.
• Lead the delivery of the foundational work needed to enable the Data Engineering team and its capabilities to serve stakeholders across the organization.
• Partner with the Head of Analytics to ensure your team has a suitable engineering strategy to serve its business objectives.
• Partner with other engineering and product leads in the organization to understand their data needs.
• Implement strategies and processes which help Data Engineers work effectively together, maintain a sustainable workflow, and ensure the stability of our Analytics systems.
• Provide feedback and set goals for your team to help them develop and grow.
• Guide the evolution of the practices and culture in the team, applying modern agile ways of working to help maintain a sustainable pace of work and foster a culture of self-improvement.
• Contribute to an effective and diverse recruiting pipeline, identify and develop the data engineering talent of tomorrow.

What you should offer

• Demonstrated experience in creating high performing teams, and supporting the growth of the people reporting to you.
• Previous experience working in data engineering roles, delivering a stable platform for analytics and insights discovery.
• Exposure to owning and managing analytics tools (either internal tools or 3rd-party tools such as Google Analytics, Snowplow, Segment or Amplitude).
• Strong cross-functional working and communication skills, and the ability to work with stakeholders who are not engineers.
• Ability to handle multiple competing priorities in a fast-paced, product-led growth SaaS company.

Would be nice to have

• Experience in a fast-paced startup environment
• Knowledge of Data Governance principles and best practices
• ETL experience with a modern data stack: Snowflake, Fivetran/Airbyte, Snowplow, and dbt
• Cloud platform development experience (i.e.: AWS/Google)
• Familiarity with any of the following:
  • Self-service analytics tools (i.e.: Metabase/Superset)
  • Business intelligence software (i.e.: Looker/Tableau)
  • Reverse ETL tools (i.e.: Hightouch/Census)