As a Data Engineer, you will analyze, design, and implement data pipeline features and infrastructure improvements. You will write efficient, well-tested code and conduct unit and integration testing. You’ll build and optimize data ingestion and ETL/ELT processes. You’ll participate in end-to-end project delivery—from ideation to production. You’ll collaborate cross-functionally with security and product teams to embed security and compliance best practices into development processes.
This is a hands-on technical leadership role to shape the future of Moonpay's data platform. As a Senior Data Engineer on the Data Platform team, you will design, build, and optimize the core infrastructure and services that empower developers and data users. You will also mentor other engineers on the team and improve the existing data platform codebase.
You’ll play a crucial role in shaping our data infrastructure, design, build, document and maintain data pipelines to support our Data Warehouse and our Data Acquisition (IoT data) systems. You’ll uphold and contribute to the creation of standards for quality and security. This role is perfect for a data professional passionate about sustainability and eager to make a significant impact.
We are hiring a Senior Software Engineer (Data Platform Engineer) to our Data Platform team in Brazil! The Data Platform Team is responsible for building and maintaining system components that pave the way for data engineers and analysts to deliver their business objectives. This team leverages open-source software, uses cloud infrastructure and services, and builds software to accomplish its mission.
We are looking for a Data Engineer to help us build and maintain the data backbone of our trading platform. You will be working on high-volume data pipelines, ensuring the reliability and observability of our infrastructure, and preparing the system for upcoming ML initiatives. If you’ve worked with modern data stacks, enjoy building efficient pipelines, and thrive in environments where data precision and scalability matter, this role might be for you.
Architect, build, and scale the data infrastructure that powers our product. Own ingestion pipelines (NiFi 2.0 → Kafka → Iceberg → BigQuery/Motherduck) end-to-end. Design and maintain data models (star, wide-table, or Iceberg-native) to support real-time and batch analytics. Build robust CI/CD, testing, and observability for data flows (GitHub Actions, dbt tests, OpenMetadata, Sentry).
RevenueCat is searching for a Senior Data Engineer to join our Data Team, with the mission to help manage the data platform and support efforts in creating a product that will help developers make more money. The data tech stack leverages SQL and Python, infrastructure is built on AWS, and Dagster is employed for orchestration, DBT for transformations, Snowflake serves as our data warehouse, ClickHouse as event storage, and Apache Kafka to move our data around.
Join the Data Platform Team to build the foundation for analytics, operational intelligence, and AI-powered experiences. Design, build, and maintain scalable, cloud-native data pipelines for batch and streaming workloads using modern tools like Airflow, Kafka, and dbt. Ensure data reliability, observability, and trust through robust monitoring, testing, and quality enforcement.
Bridgenext is seeking a skilled and experienced Senior Database Administrator to join our team. The DBA will be expected to work autonomously and collaborate with the development team to design and build high impact projects around reporting services comprising of MSQL, MongoDB and Kafka. You will be part of a team which will have on-call duties and will need to respond to high priority incident pager.
The Staff Software Engineer, Data Ingestion will be a critical individual contributor responsible for designing collection strategies, developing, and maintaining robust and scalable data pipelines. This role is at the heart of our data ecosystem, delivering new analytical software solutions to access timely, accurate, and complete data for insights, products, and operational efficiency.