Engineering Manager, Data - Brazil - Vaga para mulheres

jobr.pro; São Paulo; Presencial; BRL 334 800 - 446 400; Tempo integral

Resumo da oferta

DoorDash in São Paulo is seeking a Data Engineering Manager to oversee enterprise-scale data solutions and lead a talented team of data engineers. This role emphasizes leadership in data architecture and collaboration across teams to drive innovation.

The ideal candidate should possess extensive experience in data engineering, have a strong background in leadership, and be proficient with tools like Snowflake and ETL orchestration. We're committed to building diverse teams that reflect the communities we serve.

Qualificações

• 10+ years of experience in data engineering or related domain.
• 2+ years of hands-on management experience.
• Familiarity with large-scale batch/real-time ETL orchestration.
• Experience growing and mentoring data teams.

Responsabilidades

• Guide the development of enterprise-scale data solutions.
• Foster an engineering culture of excellence.
• Drive innovation and success within the data engineering team.
• Collaborate with stakeholders and external partners.

Conhecimentos

Leadership

Data architecture

Communication skills

Programming languages (Python/Kotlin)

SQL

Formação académica

B.S., M.S., or PhD. in Computer Science or equivalent

Ferramentas

Snowflake

Databricks

Spark

Trino

ETL tools (Airflow, Kafka, etc.)

Descrição da oferta de emprego

About the Team

This role is part of our commitment to increase the representation of women in technology at DoorDash Brazil. We strongly encourage candidates who identify as women to apply.

We are building an engineering team where women have equitable access to opportunity, leadership, and long-term career growth within our São Paulo hub.

At DoorDash, we believe diverse teams build better products. This opportunity is designed to create greater equity in access to engineering roles and long-term career growth within our São Paulo engineering hub.

DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing data structures and data warehouse architecture, this team serves as the foundation for decision‑making at DoorDash. The focus extends to enhancing the developer experience by creating tools that support the organization's high‑velocity demands.

To lead the growing team of Data engineers we are looking for managers who are passionate about Data and are thought leaders in coaching, guiding and leading teams to make Data a winning edge for DoorDash.

About the Role

DoorDash is looking for a Data Engineering Manager to guide the development of enterprise‑scale data solutions. This manager will also act as a technical expert on all things related to data architecture to empower the greater community of data engineers, data scientists, and DoorDash partners. Your focus extends to fostering an engineering culture of excellence, empowering engineers to deliver reliable, flexible solutions at scale. Additionally, you’ll play a pivotal role in building and nurturing a top‑performing team, driving innovation and success in a dynamic, fast‑paced environment.

You’re excited about this opportunity because you will…

• You are a people leader. You thrive in hiring, building, growing and nurturing impactful business focused data teams
• You are a technology leader. You drive the technical and strategic vision for the embedded pods and foundational enablers to meet current and future needs for scale and interoperability
• You strive for continuous improvement of data architecture and development process
• You think of quick wins while planning for long term strategy and engineering excellence. You are excited about breaking down large systems into easy to use data assets and reusable components
• You are excited about cross collaboration with stakeholders, external partners and peer data leaders
• You are a planner and executioner. You know the tools to plan for short term and long term team and stakeholder success
• You think of reliability and quality as must have

We’re excited about you because you have…

• B.S., M.S., or PhD. in Computer Science or equivalent
• 10+ years of experience working in data engineering, data platform or a related domain
• 2+ years of hands‑on management experience
• Exceptional communication and leadership skills, experience hiring and growing teams with a proven ability to operate in a fast moving environment
• Experienced with performance management, coaching, mentoring and growing teams
• Familiar with programming languages Python/Kotlin and SQL
• Prior experience with Snowflake/Databricks/Spark/Trino/Pinot
• Prior experience with AWS ecosystem and large scale batch/real time ETL orchestration using Airflow, Kafka, Spark Streaming,etc.
• Familiarity with various data lake file formats such as Delta Lake, Apache Iceberg, Glue Catalog, S3,etc
• Experience with these specific technologies is not required but helpful
• Building systems directly powering online applications
• Exposure to various databases such as CockroachDB, Cassandra, and PostgreSQL
• Proficient in system design and with a strong understanding and application of AI solutions in data space

Our Commitment to Diversity and Inclusion

We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.

This position is open to candidates with disabilities. DoorDash welcomes applicants registered with the national autism registry (SisTEA) and others who seek an inclusive workplace. If you need any accommodations, please inform your recruiting contact upon initial connection.