We are looking for a Senior Data Developer located in Brazil to work on a project in the financial sector. Responsibilities include designing, developing, and maintaining scalable data pipelines, ensuring data integrity, documenting data workflows, and implementing data governance practices.

A talented and motivated Senior Data Engineer is needed to join the growing team to be instrumental in designing, developing, and maintaining data infrastructure and pipelines ensuring the efficient and reliable flow of data throughout the organization, collaborating closely with software development, analytics, and product teams to drive success.

As a Data Engineer you will play a critical role in the design, implementation, and maintenance of our data infrastructure and pipelines. You'll collaborate closely with cross-functional teams including engineering, product, and revenue to ensure that our data is accurate, accessible, and reliable for making informed business decisions.

The company is looking for an experienced Data Engineer with strong expertise in Python and SQL. This role requires hands-on experience with AWS services, big data processing, and distributed computing. The Data Engineer will be responsible for building and optimizing data pipelines and integrating various data sources.

Design, develop, and maintain scalable data pipelines using Python, Spark, and Databricks. Integrate data from various sources into a unified data warehouse, ensuring data quality and governance. Optimize Spark jobs, implement CI/CD pipelines, and collaborate with stakeholders to deliver data solutions.

Join StackAdapt's growing backend engineering team as a Senior Data Engineer and help build a new data engineering initiative to solve a hard and complex big data problem, leveraging new technologies. You will build first and third-party data integrations with external data sources and architect scalable low-latency backend systems and big data pipelines. You will also promote software development best-practices and conduct code reviews.

Join our engineering team as a Senior Data Engineer to play an instrumental role in the construction and maintenance of data collection systems, pipelines and management tools, ensuring scalability, flexibility, and efficiency using pipeline authoring tools like Metaflow and Spark.

Improve data processing pipelines from performance, cost and correctness standpoints. Contribute to the development of the new data platform. Collaborate with platform and ML teams to create ETL pipelines that efficiently deliver clean and trustworthy data. Design and optimize data models based on business and engineering needs.

Unlock offline & real-time access to trillions of data points for our ML and Data Science teams by managing, expanding, and optimizing our feature store that enables feature engineering, multi-TB scale training jobs, and offline / real-time inferencing. Support PB scale data operations on the feature store using Apache Spark, Spark Structured Streaming, Kafka, and Ray. Partner with other teams and business stakeholders to deliver ML and AI initiatives.

Architect data models to drive performance metrics and business analytics, develop reporting practices to enable decision making, and build dashboards to drive customer analytics. You will also deliver internal reports for Archive's finance and growth teams and manage ad hoc data requests. We use SQL, Python, Spark, PostgreSQL, Palantir Foundry, Hex, Snowflake, and AWS.