About the Role
Role details below.
Responsibilities
- Deliver data as a product - provide impactful data solutions and features that enhance our data consumer experience.
- Lead major business data processes, pipelines, and infrastructure projects, owning both functional and non functional requirements.
- Maintain a high bar for technical excellence by contributing to core architectural decisions and demonstrating mastery of modern data processing methods.
- Own the Data Engineering Group relationship with business stakeholders to ensure alignment between data engineering initiatives and business objectives.
- Work closely with Data Science, Data Analysts, Product Managers, Architects, and Engineering Leads to define clear roadmaps and priorities for the team.
- Lead and mentor a team of passionate and talented data engineers, fostering their growth and development.
- Manage employee career development by providing coaching and mentoring, continuous performance feedback, collaborating with employees on their objectives, and providing a clear path for progression through personal development plans.
- Conduct code and architecture design reviews to maintain a healthy balance between features and technical debt.
- Continuously learn and improve your professional and managerial skills to drive the team's success.
Requirements
- Extensive experience collaborating with remote business stakeholders (Product, Data Analytics teams, Data Science, Marketing), effectively owning their data needs end to end, and aligning data solutions to support critical business objectives.
- Demonstrated track record of at least 4 years in a leadership role, successfully managing teams of 4+ data engineers; showcasing the ability to attract, inspire, and motivate talented individuals while building knowledge redundancy within the team.
- At least 8 years of proven experience in data engineering, showcasing a robust understanding of data architecture, ETL processes, and data warehousing principles.
- Hands-on proficiency with leading data engineering tools and technologies, including SQL, Python, Apache Spark, and other relevant frameworks.
- Familiarity with cloud computing platforms, especially AWS, for the development and deployment of data solutions.
- Strong grasp of data modeling concepts and proven experience in designing data solutions using cloud tools.
- Proven expertise in establishing data observability frameworks to monitor data health alongside a commitment to rigorous automated unit and integration testing for all data transformation logic.
- Strong sense of ownership and great leadership capabilities.
- Strong communication skills that help you to build trust, resolve conflicts, and provide feedback.
Nice to Have
- Experience working with Databricks.
Work Arrangement
Hybrid
