Remote Data Jobs • Terraform

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.

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.

Develop our scalable, cloud-based data platform for analytics and business intelligence, leveraging state-of-the-art data technologies. Shape an AWS-based data processing, ingesting data from our internal backend services as well as from third parties. Extend our lakehouse empowering various teams in decision-making, driving innovation, performance optimization, and strategic objectives. Prepare and clean structured and unstructured data and develop high-quality data models for advanced analytics, and AI use cases.

As a Senior Software Engineer on the Knowledge Enrichment Team, you will evolve BenchSci’s Knowledge Graph, integrate public life science data, and operationalize production-grade data pipelines. Key responsibilities include scaling data pipelines, managing biological data sources, and collaborating with ML and data engineers to solve complex data mining challenges.

You will partner with stakeholders across different product domains, infrastructure, and leadership, driving data related technical problems at scale. Design and implement maintenance automations for different data stores, this includes automations for upgrades, backups, migrations … etc. You will ensure Data stores scalability and reliability through proactive analysis and thorough capacity planning.

The Data Platform team at Pismo integrates data produced by Pismo's Banking as a Service/Payments platform with its clients through batch processing or near real-time events with a robust, low-latency, and 100% cloud-based architecture. As a senior technical contributor on Pismo’s data stack, you'll lead the design and development of robust, scalable data pipelines using modern Big Data frameworks and champion engineering excellence in a remote position.

The ideal candidate will be excited to take on the challenge of processing, storing and delivering the entire health records of millions of patients, adopting tools to handle growing scale, and ensuring high data quality and freshness. As part of the core Zus platform, the Costco team has needed to rapidly innovate to stay ahead of data volumes that grow at 10x per year.

We’re looking for a self-motivated, highly driven Software Engineer with a strong understanding of low-level distributed systems concepts. You will architect high-throughput solutions that power our most critical operations, ensuring scalability and efficiency. You will also expand and enhance our self-service platform, collaborating with cross-functional teams to fuel our AI, ML, and analytics goals.

We are seeking a senior-level Airbyte expert to act as our lead advisor and specialist for all things data movement; you will partner with our platform engineering team to solve our most complex Airbyte challenges. Your primary focus will be on developing and troubleshooting connectors, advising on best practices for scaling and reliability, and empowering our internal team with your deep expertise.

The squad is responsible for developing analytics, AI, and machine learning products at Pismo and supports the company’s data-driven decision-making. As a Data & Insights Analyst, you will design, build and maintain scalable and automated data pipelines and support analytics and machine learning workflows across different teams.