Data Engineer

Software Engineer, Data

Airtable

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. At Airtable, we're passionate about democratizing software creation — empowering anyone to build powerful, flexible tools without writing code. With our shift to an AI-native platform, customers can now generate full apps and deploy AI agents directly into their workflows. Data engineering plays a critical role in this evolution by delivering the insights our teams rely on to improve user experience, measure agent impact, and understand how the business is performing at scale. As a Software Engineer, Data at Airtable, you'll make an enormous contribution to our data engineering efforts. You'll design and own mission-critical data pipelines to enable decision-making, partner with company leaders to create scalable data solutions, and launch innovative alerting and visualization solutions. THE TEAM Our team is embedded in how Airtable understands itself as a business, working closely with Data Science and Analytics. What's unusual here: the platform you're instrumenting is the same one your customers use every day. When Airtable ships a new AI agent capability, you're among the first to wire it up, measure its adoption, and influence what gets built next. Product & AI Data Infrastructure This team builds and owns the foundational data pipelines that power product analytics across Airtable. As Airtable shifts to an AI-native platform, our work increasingly involves instrumenting and measuring AI product usage, building event pipelines for AI agents, surfacing AI-native adoption metrics in core business tables, and developing AI-powered data discovery tooling, including vector search over our catalog metadata. We partner closely with product analytics, product engineering, and data infrastructure to turn business questions into well-modeled, trustworthy data. WHAT YOU'LL DO * Work across our engineering organization and stakeholders from data science, growth, sales, marketing, and product to understand the data needs of the business and produce pipelines, data marts, and other solutions that enable better decision-making. * Design and maintain our foundational business tables in order to simplify analysis and reporting across the entire company, including AI usage metrics surfaced to executive stakeholders. * Use AI tools as a daily part of how you work, from LLM-assisted pipeline development and debugging to exploring our catalog through AI-powered discovery, and bring a curiosity for where this tooling is heading next. * Build and enforce a pattern language across our data stack, ensuring pipelines and tables are consistent, accurate, and well-understood. * Continue to improve the performance and reliability of our data warehouse. * Partner with data scientists, analytics engineers, and business stakeholders to translate ambiguous business questions into well-scoped data solutions. WHO YOU ARE * You have 3-8+ years of professional experience designing, creating, and maintaining scalable data pipelines, preferably in Airflow. * You've wrangled enough data to understand how often the complex systems that produce it can go wrong, and you build with that in mind. * You are proficient in at least one programming language (preferably Python) and are willing to pick up others as the work demands. * You are highly effective with SQL and understand how to write and tune complex queries. * You're genuinely curious about how AI is reshaping data engineering and you're actively experimenting, not just watching from the sidelines. Whether that's using LLMs to write and debug pipelines faster, thinking through how to model agent behavior as data, or exploring what smarter data discovery could look like, you bring enthusiasm for figuring it out. * You're passionate and thoughtful about building systems that enhance human understanding. * You communicate with clarity and precision in written form and have experience conveying findings through graphs and visualizations.   ---------------------------------------------------------------------------------------------------------------------------------- Compensation awarded to successful candidates will vary based on their work location, relevant skills, and experience. Our total compensation package also includes the opportunity to receive benefits, restricted stock units, and may include incentive compensation. To learn more about our comprehensive benefit offerings, please check out Life at Airtable. For work locations in the San Francisco Bay Area, Seattle, New York City, and Los Angeles, the base salary range for this role is: $179,500—$221,500 USD For all other work locations (including remote), the base salary range for this role is: $162,000—$199,800 USD Please see our Privacy Notice for details regarding Airtable’s collection and use of personal data relating to the application and recruitment process by clicking here. For applicants that live in or have a link to Australia, please see this Privacy Collection Statement for details regarding Airtable's collection and use of personal data relating to the application and recruitment process. 🔒 Stay Safe from Job Scams All official Airtable communication will come from an @airtable.com email address. We will never ask you to share sensitive information or purchase equipment during the hiring process. If in doubt, contact us at hr@airtable.com. Learn more about avoiding job scams here.

Senior Software Engineer - Distributed Data Systems

Databricks

P-59 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. What we look for: * 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 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 $166,000—$225,000 USD 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 click here. 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.

Staff Software Engineer - Distributed Data Systems

Databricks

P-186 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. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. 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. 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: Deliver 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. What we look for: * BS in Computer Science, related technical field or equivalent practical experience. * Optional: MS or PhD in databases, distributed systems. * Comfortable working towards a multi-year vision with incremental deliverables. * Driven by delivering customer value and impact. * 8+ 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 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 $192,000—$260,000 USD 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 click here. 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.