Senior Staff Software Engineer/Principal Software Engineer - Databases

Sorry, this job was removed at 09:55 p.m. (CST) on Friday, Dec 13, 2024
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Berlin
Internship
Big Data • Machine Learning • Software • Analytics • Big Data Analytics
The Role

P-1127

Summary

We are hiring a Senior Staff Software Engineer/Principal Software Engineer for Databricks' Engineering team reporting to an Engineering Leader.You will be part of the Databricks engineering organization, working on one the most important products here within Databricks while working with teams that develop Databricks products and features for thousands of enterprises worldwide as well. As a software engineer, you will join as a founding member of our Berlin site (fully remote) but really as a founding team for our multi-year journey to achieve our Lakehouse vision. You will be involved in the entire development cycle and exemplify all core Databricks values (own-it, data decide, teamwork, customer-obsessed).

Key Characteristics

As an engineer at Databricks, you will build the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science.

Job Description

At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions.

Our engineering teams build highly technical products that fulfill real, important needs in the world. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

The Impact you will have:

  • Solve real business needs at large scale by applying your software engineering.
  • Deliver a highly scalable, available, and fault-tolerant engine processing hundreds of TB of data daily across thousands of customers
  • Low level systems debugging, performance measurement & optimization on large production clusters.
  • Build architecture design, influence product roadmap, and take ownership and responsibility over new projects.
  • Introduce tools to allow greater automation and operability of services.
  • Use your deep experience to help prevent and investigate production issues.
  • Plan and lead complicated technical projects that work with several teams within the company.
  • Contribute as a Technical Team Lead by mentoring others, lead sprint planning, delegating work and assignments to team members and participate in project planning.

What we look for:

  • 15+ years industry experience building and supporting large-scale distributed systems.
  • Comfortable working towards a multi-year vision with incremental deliverables.
  • Motivated by delivering customer value and impact.
  • Strong foundation in algorithms and data structures and their real-world use cases.
  • Experience driving company initiatives towards customer satisfaction.
  • BS/MS/PhD in Computer Science or related majors, or equivalent experience.

Please Note: Fraudulent job postings and job scams are increasingly common. Due to reports of phishing, we’re requesting that all Databricks applicants apply through our official Careers page at databricks.com/company/careers. All official communication from Databricks will come from email addresses ending with @databricks.com or @goodtime.io (our meeting tool)." 

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.

The Company
New York, NY
2,200 Employees
On-site Workplace
Year Founded: 2013

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.

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