About the Team DoorDash is a data-driven organization and relies on timely, accurate, and reliable data to drive many business and product decisions. The Data Platform owns all the infrastructure necessary to run an operationally efficient analytical data stack. The Core Data part of this includes data ingestion (batch and real-time), data compute & transformation, data storage (warehouse, data lake, OLAP, etc.), querying infrastructure as well as data compliance, quality, and governance. The adjacent areas of major focus are Machine Learning Infrastructure and workflow, Experimentation Platform, Knowledge Graphs, and various Data Science and Analytics related tooling.
About the Role As a Senior Engineering Manager in DoorDash's Core Data Platform organization, you will be responsible for the most critical long-term technical roadmap of the organization. You will use your skills and experience in guiding the engineers and the management leadership on the right technical choices, mentor several senior engineers, and hold a high bar of technical competency. You will be taking a very active part in build vs buy strategies and work with several leading Data Vendors and solution providers in the industry. You will report into the Senior Director of Engineering, Data Platform as part of our Data organization in Engineering.
You're excited about this opportunity because you will - Drive vision & strategy for building the Core Data Platform charter and position it to handle the challenges of a rapidly growing business.
- Bring your expertise in building and operating high-scale systems with a focus on reliability and quality of analyzed data.
- Lead a well-run, successful team via coaching, mentoring, and providing technical and career guidance.
- Build, sustain, and grow a diverse team to address the growing needs of the organization.
- Build data-intensive solutions that are used by DoorDash engineers, data scientists, analysts, or business users from across the company. Drive and deliver the ongoing product vision of data products.
- Think in terms of building data products and not systems. Excel at driving the engineering vision, strategy, and execution for an organization consisting of multiple teams and sub-teams.
- Be a technology leader. Excel at mentoring and guiding a fast-growing organization in setting the right architectural patterns, handling build vs buy decisions, working with various vendors in the data solutions space, and making judicious investments in the right areas anticipating what the company needs a few years down the road.
- Think of quick wins while planning for long-term strategy and engineering excellence. Excited about breaking down large systems into manageable, sustainable components that can be iterated on.
- Strive for continuous improvement of data architecture and development process.
- Be excited about cross-collaboration with stakeholders, external partners, and peer data leaders.
- Love rolling up your sleeves to get down to the lowest level of detail.
- Foster a positive and supportive work culture.
We're excited about you because you have - B.S., M.S., or PhD in Computer Science or equivalent.
- 10+ years of industry experience.
- 5+ years of experience in an engineering management role.
- Extensive experience building and operating scalable, fault-tolerant, distributed systems in the area of large-scale data-intensive applications.
- Experience with a range of large-scale (multiple PetaBytes) data systems such as data processing, complex/high volume real-time insights, data quality and reliability frameworks, cost efficiency, etc. The following areas are representative of the breadth of data technologies in which familiarity would be optimal (Experience with each of these specific technologies or similar alternatives is not required but helpful):
- Apache Spark, Airflow, Trino, Pinot, Flink, Kafka.
- Data Warehousing and Data Lake technologies such as Snowflake, Databricks, various table formats such as Iceberg or Delta Lake.
