The Accounting/Revenue Operations Data Engineering team at DoorDash plays a critical role in building and maintaining the required datasets for revenue recognition, book close process as well as enabling our accounting team to derive insights from our revenue data.This team will be part of the broader Financial Intelligence Team. This role will interface with our Accounting/Revenue teams to build out scalable data pipelines as well as to automate our back office operations.
About the Role
DoorDash is looking for a hands-on Data Engineering Manager, to act both as a technical leader when scaling data infrastructure and working with your team. This manager will guide the greater data engineering team, analysts, accounting/revenue and DoorDash partners toward necessary structured data, reporting and insights.
You're excited about this opportunity because you will...
- Provide expertise across data warehouse architecture and infrastructure maintenance that supports an evolving set of products with data infrastructure engineering teams
- Balance both managerial and technical goals simultaneously, including 1+1's, technical mentorship, and recruitment
- Collect, process, and clean data from different sources using SQL, Python, or other scripting languages
- Work with teams to automate reporting and build a strong reporting architecture
- Own and manage a portfolio of our tools which empower analysts and data scientists across the company
- Continuously optimize ETL jobs to hit performance targets
- Build data governance with scalable processes, useful data definitions, and effective project planning
We're excited about you because...
- 7+ year of technical experience working in business intelligence, analytics, data engineering, or a similar role
- 3+ years of direct-report management, while juggling BOTH technical and managerial tasks, including 1+1's, technical mentorship, and recruitment participation
- A hands-on approach to closing gaps in technical architecture and project execution, able to code complex SQL queries, knowledge of python
- Project management of scalable data engineering architecture and review bugs with engineering teams that achieve business objectives
- Knowledge of relational databases and frameworks (Snowflake, Redshift, PostgreSQL, Git, Airflow) and big data structures
- Familiar with Jira, SDLC, and cloud technologies
- Experience using and building solutions to support various reporting and data user tools (Tableau, Looker, etc.)
- Experience with data generated by proprietary software systems and industrial solutions (SFDC, Segment, etc.)
- Experience working with teams to assess their data needs
- Hands-on leader and help the team internalize best practices by example