Sr. Manager, Data Engineering
hace 5 meses
**ABOUT THE ROLE AND OUR TEAM**:
The Knot Worldwide’s Data team is looking for a hands-on, highly motivated, highly energetic team player with a strong analytical mindset to join as a Senior Manager of Data Engineering supporting end-to-end analytics & reporting needs for our business, leading a team of Data Engineers.
This role will be partnering closely with our stakeholders and also with other Data teams to develop data models, pipelines, and data-driven solutions that enable deep analysis for our Business Domains (Product, Marketing, and Revenue) and supporting AI/ML initiatives led by our Data Science team.
We see the Senior Manager of Data Engineering as a hybrid role that combines elements of data engineering, business intelligence, and data analysis. You will be responsible for mentoring a team of data engineers, building (leading) end-to-end data pipelines using tools like dbt, Airbyte, Airflow, Snowflake, and other modern data stack components. This role requires proficiency in SQL, python, data modeling, and data transformation, but also leadership, collaboration skills and business acumen as they play a crucial role in enabling data-driven decision-making within our organization.
**RESPONSIBILITIES**:
- Lead and mentor a team of data engineers, playing a hands on role to design, build, and maintain end-to-end data pipelines that collect, process, and analyze large datasets, including but not limited to, behavioral tracking, customer profiles, financial & e-commerce transactions, CRM, and advertising
- Participate in overall architecture and strategy for deploying our end-to-end data pipelines and adhering to best practices supporting our CI/CD processes in an agile environment
- Work closely with senior management to define the data engineering strategy, aligning it with the overall business objectives and technological roadmap
- Develop and implement data models for optimal storage, retrieval and analysis of data
- Collaborate with DevOps and infrastructure teams to deploy and manage data platforms and services in cloud environments (AWS & Snowflake)
- Optimize and tune database queries and data processing workflows for performance and efficiency
- Foster data governance practices, ensuring data privacy, security & compliance, and documenting data pipelines, transformations, and models
- Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver data solutions that meet business needs
- Research and evaluate new technologies and tools to enhance the data engineering infrastructure
- Participate in code reviews, documentation, and knowledge-sharing activities
**SUCCESSFUL CANDIDATES HAVE**:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- 5+ years of experience holding crucial roles in leading a team of data engineers to architect, design, develop, and maintain scalable and reliable data infrastructure and pipelines while providing guidance, coaching, and support to ensure their professional growth and development.
- 7+ years experience including design, development, data management, administration, and support building data models with recent experience working with dbt and Snowflake
- 5+ years experience in data integration & orchestration using Airbyte & Airflow or similar tools
- Solid understanding of modern data engineering and architecture concepts and practices including deep knowledge of data warehousing, data pipelines, data marts, and data integration techniques and tools
- Advanced proficiency using SQL developing dimensional models supporting EDW and modern data architecture approaches such as Data Lake/Lakehouse
- Proficiency using Git, GitHub and Python
- Experience using data from Salesforce, Segment & GA is a plus
- Must be self-motivated and able to work both independently and with others
- Positive attitude and ability to receive and provide objective and constructive feedback
- Strong organizational and troubleshooting skills with attention to detail, and curiosity to detect and explain data anomalies
- Excellent leadership, communication, and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and stakeholders
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