Senior Software Engineer - Distributed Data Systems

Databricks
Bellevue, WA, United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$157,700.0 - $213,800.0
Working hours
Regular working hours

Tech stack

Query Performance Java (Programming Language) Artificial Intelligence Amazon S3 Data Analysis Big Data C++ (Programming Language) Cloud Storage Databases Information Engineering Extract Transform Load (ETL) Data Warehousing
+21 more
Distributed Data Store Distributed Systems Design of User Interfaces Apache Hadoop Human-Computer Interaction Machine Learning Open Source Technology Query Optimization Software Engineering SQL Databases Virtual Machines Data Storage Management Data Storage Technologies Rollup Apache Spark Data Lakes Information Technology Low Latency Drilldown Data Pipelines Databricks

Job description

At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers - and customer obsessed - we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we’re only getting started.

Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building 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.

Below are some example projects:

Apache Spark: Develop the de facto open source standard framework for big data.

Data Plane Storage: Provide reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store.

Delta Lake: A storage management system that combines the scale and cost-efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real-world data engineering architecture.

Delta Pipelines: It’s difficult to manage even a single data engineering pipeline. The goal of the Delta Pipelines project is to make it simple and possible to orchestrate and operate tens of thousands of data pipelines. It provides a higher level abstraction for expressing data pipelines and enables customers to deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines.

Performance Engineering: Build the next generation query optimizer and execution engine that’s fast, tuning free, scalable, and robust.

Requirements

Software Engineering, Distributed Computing, Artificial Intelligence (AI), User Interface/Experience (UI/UX), Virtual Machine (VM), Process Improvement, Data Analysis, Machine Learning, Data Science, Data Storage, * BS (or higher) in Computer Science, related technical field or equivalent practical experience.

  • Comfortable working towards a multi-year vision with incremental deliverables.
  • Motivated by delivering customer value and impact.
  • 5+ years of production level experience in either Java, Scala or C++.
  • Strong foundation in algorithms and data structures and their real-world use cases.
  • Experience with distributed systems, databases, and big data systems (Apache Spark, Hadoop).

Pay Range Transparency

Benefits & conditions

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected 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 anticipates utilizing 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.

Local Pay Range

$157,700-$213,800 USD

About Databricks, 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 click here.

About the company

Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

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