Data Engineer 457 views

At Databricks you will work on some of the most complex distributed processing and machine learning problems in the world and their customers challenge them daily with interesting new big data and AI use cases. As a Data Engineer at Databricks, you will report directly to the UKI Director for Architecture, Consulting, and Enablement. You will shape the future big data and the machine learning landscape for leading Fortune 500 organizations.

You will be in a customer-facing role that requires deep hands-on expertise in Apache Spark™ and data engineering, along with a variety of knowledge of the big data ecosystem. You will guide their largest customers, for example implementing pipelines from data engineering through model building and deployment. A successful Solutions Consultant is curious and excels in collaboration. 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 top big data conferences.

The Impact You Will Have

• Guide strategic customers as they implement transformational big data projects, including end-to-end development and deployment of industry-leading big data and AI applications
• Use your expertise in data engineering best practices to guide customers to do the same, through building proofs of concept and prototypes and even pair-programming with customer teams
• Implement migration of workloads from 3rd party databases and data platforms to Apache Spark™
• Promote Apache Spark™ and Databricks, Delta Lake, and MLflow across the developer community through meetups and conferences
• Coordinate with Account Executives, Customer Success Engineers, and Solution Architects for expanding the use of Databricks platform within strategic enterprise customers weekly
• Assist the Professional Services leader and project managers with the level of effort estimation and mitigation of risk within customer proposals and statements of work
• Assure that Databricks best practices are being used within all projects and that their quality of service and implementation is strictly followed
• Knowledge transfer, enablement, and mentoring of other team members, customers, and partners

What They Look For

They are hiring at a range of levels and adjust their competency expectations, however for a senior-level role they would expect the following:

• Deep hands-on expertise in Apache Spark™ (Scala or Python)
• Experience with other Big Data technologies (Hadoop ecosystem, Kafka, NoSQL databases)
• Familiarity with a full range of data engineering approaches, covering theoretical best practices and the technical applications of these methods
• Experience building and deploying a range of data engineering pipelines into production, including using automation best practices for CI/CD
• Experience with cloud providers such as AWS, Azure, or GCP
• Travel will be 70-80% regionally

Benefits

• Employer contributions to the public or private health plan
• Equity awards
• Gym reimbursement
• Annual personal development fund
• Work headphones reimbursement
• Business travel insurance

About Databricks

Databricks is a data and AI company. Thousands of organizations worldwide — including Comcast, Condé Nast, Nationwide, and H&M — rely on Databricks’ open and unified platform for data engineering, machine learning, and analytics. Databricks is venture-backed and headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark™, Delta Lake, and MLflow, Databricks is on a mission to help data teams solve the world’s toughest problems. To learn more, follow Databricks on Twitter, Linked In, and Facebook.

Their Commitment to Diversity and Inclusion

At Databricks, they are committed to fostering a diverse and inclusive culture where everyone can excel. They take great care to ensure that their 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.