This position is a customer-facing role that requires deep hands-on expertise in Apache SparkTM and data engineering, along with a breadth of knowledge of the big data ecosystem.
On a weekly basis, you will guide customers through architecture, design, and implementation while aligning their technical roadmap for expanding the usage of the Databricks platform. As part of the RSA team, you will continue to strengthen your technical expertise through mentorship, learning, and internal training programs. This role can be remote, but you will be located in the job listing area and will travel up to 30% when needed. You'll report to the VP of the APJ Customer Success team. As part of joining Databricks, you will have a direct channel to the developers of Apache Spark, Delta Lake, and MLflow, and the opportunity to attend and present at top big data conferences.
The impact you will have:
- Guide strategic customers as they implement transformational big data projects, including end-to-end design, build and deployment of industry-leading big data and AI applications
- Leverage your deep expertise in data engineering best practices to guide customers to do the same, through building proofs of concept and prototypes, architecting solutions and even pair-programming with customer teams as necessary
- Architect, implement, and/or validate migration of workloads from 3rd party databases and data platforms to Apache SparkTM
- Evangelize Apache SparkTM and Databricks, Delta Lake and MLflow across developer community through meetups and conferences
- Plan and coordinate with Account Executives, Customer Success Engineers and Solution Architects for expanding the use of Databricks platform within strategic enterprise customers on a weekly basis
What we look for:
- Deep hands-on expertise in Apache SparkTM (Scala or Python)
- 5+ years experience in Design and implementation of Big Data technologies (Apache SparkTM, Hadoop ecosystem, Apache Kafka, NoSQL databases) and familiarity with data architecture patterns (data warehouse, data lake, streaming, Lambda/Kappa architecture)
- 5+ years experience working as either:
- Software Architect/Data Architect /Big Data Architect: query tuning, performance tuning, troubleshooting, and debugging Spark and other big data solutions.
- Familiarity with a full range of data engineering and architecture approaches, covering theoretical best practices and the technical applications of these methods
- Experience with building and deploying a range of data engineering pipelines into production, including using automation best practices for CI/CD
- Familiarity with databases and analytics technologies in the industry including Data Warehousing/ETL, Relational Databases, or MPP
- Experience with performance tuning, troubleshooting, and debugging SparkTM and/or other big data solutions
- Comfortable with talking up and down the IT chain of command including directors, managers, architects and developers
- Experience with cloud providers such as AWS, Azure or GCP
- Familiarity with AWS/EC2 cloud deployment models (Public vs. VPC)
- Written and verbal fluency in Mandarin would be a bonus
- Willing to travel 30-40% regionally
- Private medical, dental and optical
- Life, accident, disability and critical illness coverage
- Central Provident Fund for local nationals
- Equity awards
- Paid parental leave
- Gym reimbursement
- Annual personal development fund
- Work headphones reimbursement
- Business travel accident insurance
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.