Remote Data Jobs • Spark

Shape the future of mental health care with AI-enabled experiences, working as a Data Engineer to build and maintain data pipelines that pull information from our central storage system to train machine learning models and AI tools. Collaborate with data experts and other specialists to turn raw information into useful resources, directly supporting innovations that help more individuals get the mental health support they deserve.

As a Senior Data Engineer, you will be instrumental in shaping the future of our data platform. You will work with a global, remote-first team to build, scale, and optimize our data infrastructure using cutting-edge tools like Databricks, Spark, Terraform, and cloud platforms (AWS/Azure). Your work will empower teams to access the data they need, drive insights, and optimize business outcomes.

CI&T is looking for a talented Databricks Senior Data Architect to design, develop, and maintain scalable data pipelines and infrastructure to drive data analytics and machine learning solutions for clients. You will design and implement scalable and efficient data architecture solutions, create, test, and maintain robust data pipelines, and collaborate with data engineers, data scientists, and stakeholders.

Ryz Labs is seeking a Principal Data Engineer to design, build, and own modern data platforms end-to-end, from ingestion pipelines and cloud infrastructure through to high-quality, production-grade code. You'll pair traditional data-engineering strengths with solid software-development practices to deliver resilient data products that scale. The role involves developing robust data pipelines, engineering infrastructure, applying software-craft disciplines, and championing data quality.

You'll play a crucial role in developing and maintaining scalable data pipelines and infrastructure to drive data analytics and machine learning solutions for our clients. Responsibilities include designing data pipelines, collaborating on data architecture, optimizing performance, and ensuring data quality.

We are looking for a skilled and motivated Data Engineer to join our data team with a primary focus on orchestrating and maintaining data workflows using Dagster. In this role, you will be responsible for designing, implementing, and managing scalable and reliable data pipelines across various environments. It will entail the development of data transformation tasks and pipelines, collaborating closely with business analysts, data architects, and business stakeholders.

As a Senior Data Engineer, you will be a core contributor to the development and maintenance of scalable, secure, and high-performance data pipelines, collaborating with product, analytics, and engineering teams to ensure reliable data availability across the organization. You'll also play a critical role in mentoring junior engineers, adhering to engineering best practices, and proactively improving our data infrastructure.

As a Data Engineer at Kraken, you’ll be responsible for building and maintaining high-performance data pipelines, ensuring the reliability and scalability of our data infrastructure, and enabling teams across the company to access clean, consistent, and timely data. You’ll work with modern technologies and large-scale datasets, playing a key role in making data accessible for analytics, machine learning, and product innovation.

Serve as a senior technical contributor on Pismo’s data stack, leading the design and development of robust, scalable data pipelines using modern Big Data frameworks. Drive continuous improvement in platform performance, reliability, and cost-effectiveness, proactively identifying opportunities for innovation. Take ownership of production operations and monitoring (file-based systems), ensuring adherence to SLAs and applying best practices for observability and resilience.

The Principal Data Engineer will design, build, implement, and maintain data processing pipelines for the extraction, transformation, and loading (ETL) of data from a variety of data sources. The role will develop robust and scalable solutions that transform data into a useful format for analysis, enhance data flow, and enable end-users to consume and analyze data faster and easier.