CSQ326R34
As a Sr. Big Data Engineer in our Professional Services team, you will work with clients on short to medium-term customer engagements on their big data challenges using the Databricks Platform. You will provide data engineering, data science, and cloud technology projects that require integrating with client systems, training, and other technical tasks to help customers get the most value out of their data. You will report to the Manager, Professional Services.
The impact you will have:
- You will work on a variety of impactful customer technical Big Data projects, which may include building reference architectures, how-to's and production-grade MVPs
- Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
- Consult on architecture and design; bootstrap or implement strategic customer projects that lead to a customer's successful understanding, evaluation and adoption of Databricks.
- Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement-specific product and support issues.
What we look for:
- 10+ years experience with Big Data Technologies such as Apache Spark™, Kafka, Cloud Native and Data Lakes in a customer-facing post-sales, technical architecture or consulting role
- 6+ years of experience working on Big Data Architectures independently
- Strong experience working in the Databricks ecosystem
- Comfortable writing code in either Python or Scala.
- Experience working across Cloud Platforms (GCP / AWS / Azure)
- Documentation and white-boarding skills.
- Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
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.
Top Skills
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.
