GAQ226R150
Location: San Francisco, CA or Mountain View, CA
At Databricks Information Technology, we are a product led organization transforming the way data is sourced, designed and used to help us scale seamlessly in face of incredible growth.
You will influence technological decision-making for business teams’ data and AI strategy and roadmap. You will guide the business in identifying data needs and delivering data products for acquiring, processing and reporting such information to meet company objectives. You will be considered the go-to-expert for stakeholders on data warehousing and data intelligence. You will gather and maintain best practices that can be adopted across the broader data analytics community. You will be a part of the growing IT Data Team.
The impact you will have:
- Design/Strategy: The Staff Data Engineer is the technical owner of the data strategy and design that supports the business’s lakehouse and schemas. In this capacity, the Staff Data Engineer will typically lead a team of data engineers to design and develop data products (data pipelines, BI and AI models) to serve a variety of business use-cases.
- Collaboration: The role of a Staff Data Engineer is highly collaborative - working closely with analysts, data scientists, and other data consumers within the business. The Staff Data Engineer also works closely with other disciplines/departments and teams across the company in coming up with simple, functional, and elegant solutions that balance data needs across the business
- Analytics: The Staff Data Engineer plays an analytical role in quickly and thoroughly analyzing business requirements for reporting and analysis and translating into good technical data designs. In this capacity, the Staff Data Engineer needs to have a strong sense of metrics and analytics to establish patterns and insights to help develop a well researched design.
What we look for:
- 8+ years of related experience with a Bachelor’s degree; or 6+ years with a Master’s degree; or 4+ years with PhD; or equivalent work experience.
- Education degree in Computer Science, Statistics, Information Systems or another quantitative field.
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets. In depth knowledge of data modeling and design of schemas for read and write performance. Apache Spark™ experience is a big plus
- Advanced working knowledge and experience working with relational databases, query authoring as well as working familiarity with a variety of databases
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- Knowledge of message queuing, stream processing, API based extraction and highly scalable ‘big data’ data stores.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Hands-on experience with Python and SQL is a must
- Experience with building data pipelines from business applications like Salesforce, Marketo, NetSuite, Workday etc.
- Prior hands-on technical leadership experience is a big plus.
- Experience with Databricks Platform is a big plus
- Experience with AI/ML/Data Science is a big plus
- Knowledge of BI Tools like Tableau, Looker etc
