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
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks utilizes the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
Zone 1 Pay Range
$173,100—$265,500 USD
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
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What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
