Founding backend engineer
TL:DR
We are building a serverless infrastructure supporting on-demand, scalable and cheap data operations (e.g. analytics workload in SQL, data expectations in Python). There are three main tenets:
Ultra fast turnaround time: developer experience feels local while keeping all the benefits of the cloud.
Never take care of infra: you never have to provision resources, manage dependencies and maintain environments. Our serverless infrastructure scales automatically in your cloud and allows you to deploy on a schedule with one line of code.
Close the gap between dev and prod: you can run experimental pipelines on data samples and deploy both runtime and code with one line from your CLI, without significant differences between dev and prod environments.
We are looking to hire a generalist founding engineer with a strong focus on code understanding and building cloud-first abstractions with a keen product eye for developer UX. While we are flexible on seniority as measured through years of experience, this is a mid-senior hire.
Vision
The conversation about Big Data monopolized the discourse about data infrastructure and data engineering for quite a while. Most practitioners have been using systems and frameworks that were built by Big Data companies to handle Big Data problems.
However, across enterprises most data transformation pipelines do not get close to the biblical scale that the term Big Data hints at. A significant amount of data transformation in enterprise is not in the order of magnitude of Big Data. Data Science, Embedded Analytics, Marketing tech, Business Intelligence in enterprises often require pipelines that do not exceed the size of 100GB.
Even if a substantial part of data transformation does not in principle require complex end-to-end stacks or limitless computational power, teams are still required to build and maintain a lot of infrastructure. Several components need to be pieced together: storage, querying capabilities, orchestration, development environments, data versioning and CI/CD integrations. This state of affairs results in great integration complexity, growing maintenance overhead and rigid developer experience.
The reality is that data volumes grow much slower than our ability to provide efficient and boundless cloud computing. That’s why we envision a future where storage and compute are finally separated for good and serverless capabilities will open to new possibilities simplifying drastically the relationship between the developer and the data infrastructure. We want developers to always work in the cloud and deploy their work with one CLI line: the only thing needed to ship pipelines in production is SQL and/orPython code and an API call.
Job Description
The candidate will be responsible for helping design the foundations of our platform, working with the team to prioritize, plan and execute the company vision. In particular:
Design and develop our CLI library and SDKs to allow developers and web apps to interact with the platform. Ease-of-use, performance and reliability through all interactions are essential for success - a keen product eye is needed to guide the development process.
Improve our code intelligence capabilities, through code analysis, meta-data understanding and better abstractions for data transformation across multiple languages.
Collaborate with other developers to ensure quality of codebase and continuously improve our development cycle (CI/CD, iteration speed, security etc.).
Requirements
excellent command of Python, and one low-level programming language (keen to learn more if needed);
working knowledge of code analysis, parsing and code manipulation;
working knowledge of cloud services (AWS preferred), Docker development and commercial and/or open source serverless platforms;
experience in developing and interacting with API-first platforms, and some experience in REST, grpc and WebSocket communication;
experience in developing open source software and / or CLI- based tools to interact with APIs is a plus.
We are backed by top tier investors (Innovation Endeavors, South Park Commons) and supported by world-class angels coming from Stanford, NVIDIA, Redis Labs, Docker, AWS and founders from some of the best startups in the space.
We are an early stage startup with a heavy technical mission. We build exciting features and tackle hard problems in the data space. Early stage comes with hard problems, fast changing roadmaps and quick iterations: willingness to continually learn new things, challenge conventional wisdom, and working with blurry lines are imperative.
We're an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation.
Founding backend engineer
TL:DR
We are building a serverless infrastructure supporting on-demand, scalable and cheap data operations (e.g. analytics workload in SQL, data expectations in Python). There are three main tenets:
Ultra fast turnaround time: developer experience feels local while keeping all the benefits of the cloud.
Never take care of infra: you never have to provision resources, manage dependencies and maintain environments. Our serverless infrastructure scales automatically in your cloud and allows you to deploy on a schedule with one line of code.
Close the gap between dev and prod: you can run experimental pipelines on data samples and deploy both runtime and code with one line from your CLI, without significant differences between dev and prod environments.
We are looking to hire a generalist founding engineer with a strong focus on code understanding and building cloud-first abstractions with a keen product eye for developer UX. While we are flexible on seniority as measured through years of experience, this is a mid-senior hire.
Vision
The conversation about Big Data monopolized the discourse about data infrastructure and data engineering for quite a while. Most practitioners have been using systems and frameworks that were built by Big Data companies to handle Big Data problems.
However, across enterprises most data transformation pipelines do not get close to the biblical scale that the term Big Data hints at. A significant amount of data transformation in enterprise is not in the order of magnitude of Big Data. Data Science, Embedded Analytics, Marketing tech, Business Intelligence in enterprises often require pipelines that do not exceed the size of 100GB.
Even if a substantial part of data transformation does not in principle require complex end-to-end stacks or limitless computational power, teams are still required to build and maintain a lot of infrastructure. Several components need to be pieced together: storage, querying capabilities, orchestration, development environments, data versioning and CI/CD integrations. This state of affairs results in great integration complexity, growing maintenance overhead and rigid developer experience.
The reality is that data volumes grow much slower than our ability to provide efficient and boundless cloud computing. That’s why we envision a future where storage and compute are finally separated for good and serverless capabilities will open to new possibilities simplifying drastically the relationship between the developer and the data infrastructure. We want developers to always work in the cloud and deploy their work with one CLI line: the only thing needed to ship pipelines in production is SQL and/orPython code and an API call.
Job Description
The candidate will be responsible for helping design the foundations of our platform, working with the team to prioritize, plan and execute the company vision. In particular:
Design and develop our CLI library and SDKs to allow developers and web apps to interact with the platform. Ease-of-use, performance and reliability through all interactions are essential for success - a keen product eye is needed to guide the development process.
Improve our code intelligence capabilities, through code analysis, meta-data understanding and better abstractions for data transformation across multiple languages.
Collaborate with other developers to ensure quality of codebase and continuously improve our development cycle (CI/CD, iteration speed, security etc.).
Requirements
excellent command of Python, and one low-level programming language (keen to learn more if needed);
working knowledge of code analysis, parsing and code manipulation;
working knowledge of cloud services (AWS preferred), Docker development and commercial and/or open source serverless platforms;
experience in developing and interacting with API-first platforms, and some experience in REST, grpc and WebSocket communication;
experience in developing open source software and / or CLI- based tools to interact with APIs is a plus.
We are backed by top tier investors (Innovation Endeavors, South Park Commons) and supported by world-class angels coming from Stanford, NVIDIA, Redis Labs, Docker, AWS and founders from some of the best startups in the space.
We are an early stage startup with a heavy technical mission. We build exciting features and tackle hard problems in the data space. Early stage comes with hard problems, fast changing roadmaps and quick iterations: willingness to continually learn new things, challenge conventional wisdom, and working with blurry lines are imperative.
We're an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation.
Founding backend engineer
TL:DR
We are building a serverless infrastructure supporting on-demand, scalable and cheap data operations (e.g. analytics workload in SQL, data expectations in Python). There are three main tenets:
Ultra fast turnaround time: developer experience feels local while keeping all the benefits of the cloud.
Never take care of infra: you never have to provision resources, manage dependencies and maintain environments. Our serverless infrastructure scales automatically in your cloud and allows you to deploy on a schedule with one line of code.
Close the gap between dev and prod: you can run experimental pipelines on data samples and deploy both runtime and code with one line from your CLI, without significant differences between dev and prod environments.
We are looking to hire a generalist founding engineer with a strong focus on code understanding and building cloud-first abstractions with a keen product eye for developer UX. While we are flexible on seniority as measured through years of experience, this is a mid-senior hire.
Vision
The conversation about Big Data monopolized the discourse about data infrastructure and data engineering for quite a while. Most practitioners have been using systems and frameworks that were built by Big Data companies to handle Big Data problems.
However, across enterprises most data transformation pipelines do not get close to the biblical scale that the term Big Data hints at. A significant amount of data transformation in enterprise is not in the order of magnitude of Big Data. Data Science, Embedded Analytics, Marketing tech, Business Intelligence in enterprises often require pipelines that do not exceed the size of 100GB.
Even if a substantial part of data transformation does not in principle require complex end-to-end stacks or limitless computational power, teams are still required to build and maintain a lot of infrastructure. Several components need to be pieced together: storage, querying capabilities, orchestration, development environments, data versioning and CI/CD integrations. This state of affairs results in great integration complexity, growing maintenance overhead and rigid developer experience.
The reality is that data volumes grow much slower than our ability to provide efficient and boundless cloud computing. That’s why we envision a future where storage and compute are finally separated for good and serverless capabilities will open to new possibilities simplifying drastically the relationship between the developer and the data infrastructure. We want developers to always work in the cloud and deploy their work with one CLI line: the only thing needed to ship pipelines in production is SQL and/orPython code and an API call.
Job Description
The candidate will be responsible for helping design the foundations of our platform, working with the team to prioritize, plan and execute the company vision. In particular:
Design and develop our CLI library and SDKs to allow developers and web apps to interact with the platform. Ease-of-use, performance and reliability through all interactions are essential for success - a keen product eye is needed to guide the development process.
Improve our code intelligence capabilities, through code analysis, meta-data understanding and better abstractions for data transformation across multiple languages.
Collaborate with other developers to ensure quality of codebase and continuously improve our development cycle (CI/CD, iteration speed, security etc.).
Requirements
excellent command of Python, and one low-level programming language (keen to learn more if needed);
working knowledge of code analysis, parsing and code manipulation;
working knowledge of cloud services (AWS preferred), Docker development and commercial and/or open source serverless platforms;
experience in developing and interacting with API-first platforms, and some experience in REST, grpc and WebSocket communication;
experience in developing open source software and / or CLI- based tools to interact with APIs is a plus.
We are backed by top tier investors (Innovation Endeavors, South Park Commons) and supported by world-class angels coming from Stanford, NVIDIA, Redis Labs, Docker, AWS and founders from some of the best startups in the space.
We are an early stage startup with a heavy technical mission. We build exciting features and tackle hard problems in the data space. Early stage comes with hard problems, fast changing roadmaps and quick iterations: willingness to continually learn new things, challenge conventional wisdom, and working with blurry lines are imperative.
We're an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation.
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