What you will be doing:
- Manage a team of data engineers and analytics engineers, overseeing their professional development, performance, and career growth
- Implement the product roadmap and project plans established by leadership
- Oversee the team's analytics engineering practices, ensuring adherence to data modeling standards and transformation best practices
- Monitor project progress and ensure timely delivery of analytics solutions
- Facilitate effective communication between team members and across departments
- Conduct regular 1:1s, provide feedback, and support team members' professional development
- Ensure code quality through code reviews and adherence to established analytics engineering standards
- Manage resource allocation and team capacity to meet project commitments
- Support the implementation of data testing frameworks and quality validation processes
- Enforce data governance, quality, and security protocols within the team's work
- Hire new team members as needed and integrate them effectively into the team
- Identify skill gaps and coordinate appropriate training opportunities
- Remove obstacles and resolve conflicts to maintain team productivity
- Report on team performance and project status to senior leadership
- Ensure smooth collaboration between analytics engineering and other technical teams
What you should bring:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- Min 8-10 years experience with 6+ years in data/analytics engineering roles, with 3+ years of people management experience
- Understanding of analytics engineering principles and data modeling techniques
- Familiarity with our core technologies (AWS, Snowflake, Databricks, Python, SQL)
- Experience managing teams working with data transformation frameworks
- Strong people management skills with focus on team development
- Ability to effectively manage resources and track project progress
- Experience mentoring junior engineers in analytics engineering practices
- Ability to work effectively in a globally distributed team environment
- Strong communication and interpersonal skills
- Organized approach to managing multiple priorities and deadlines
- Experience with performance management and professional development planning
Technologies we use:
- AWS
- Amazon Managed Workflows for Apache Airflow (MWAA)
- Snowflake
- Databricks
- Python
- SQL
- dbt (data build tool)
- Terraform
- Data visualization tools
- Project management and collaboration tools
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