Data Engineering Manager
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Job Description
Data Engineering Manager leading teams to enable data engineers for high-quality data solutions. Collaborating cross-functionally to drive technical decisions and achieve impactful results.
Responsibilities:
- Enable our data engineers to become highly productive members of their cross-functional teams, empowering them to ship high-quality, reliable data platforms and pipelines on a daily basis.
- Grow the teams by attracting great talent from your network.
- Foster an inclusive and caring culture where everyone can do their best work.
- Provide regular 1:1 coaching and feedback to tap into the potential of all your team members and help them thrive and reach their aspirations.
- Be a strategic partner to product managers, machine learning engineers, and other stakeholders within your domains and ensure that we are making the correct data architecture and platform decisions that balance short and long term goals.
- Ensure suitability of the data architecture, pipelines, and data models within your domains to enable longer term product, analytics, and machine learning goals.
- Work closely with the other Product & Engineering leaders on strategy, technology and people, including improving our data engineering practices and introducing capabilities that can accelerate data access, reliability, and unlock new product and data-driven opportunities
Requirements:
- Passionate about climate
- Experience working in a high growth scaleup environment
- Product minded and able to demonstrate significant impact you have had on a business through the application of data platforms and data-driven systems
- At least 2 years experience leading and managing data engineers across multiple teams
- Experience working with the following (or similar) technologies: Python, SQL, data pipeline orchestration tools (e.g., Airflow, Dagster), data warehouses/lakehouses, Postgres DB, data pipelines
- Ability to unblock your team by contributing at a senior engineering level (e.g., reviewing data models, debugging pipelines, guiding architecture). How hands-on you'll be in this role will depend on team size and maturity
- Comfortable working in a build it, run it environment (GCP, cloud run, grafana, k8s) - or similar, with an understanding of data reliability, observability, and pipeline operations
- Strong leadership skills with the ability to mentor and coach engineers at all levels
- Excellent communication skills and ability to collaborate effectively in a cross-functional team environment
- Passion for learning and staying updated with evolving technologies and industry trends, particularly in data engineering and data infrastructure,
- Nice to haves: Experience working with maps/imagery/geospatial domains is beneficial but not essential.
Benefits:
- To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis.
- Flexible working environment with a lot of autonomy. We build our work days around our lives, not the other way around.
- Other benefits like a remote working budget, an educational budget and time to develop new skills.
- To be surrounded by an excellent, vibrant, smart team who have each other's back and believe in a culture of openness, tolerance and respect.
- Equity and a competitive salary.
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