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.

Headway is looking for a Data Engineer to help create access to affordable, quality mental healthcare across the United States. As a member of the Data Engineering team, you will collaborate with others in designing, building and implementing data pipelines that serve the core product and various stakeholders. You will be partnering with Data Science, Data Analytics and Core Infrastructure functions closely.

As a Staff Data Engineer, you will be responsible for maintaining and operating the data platform that caters to machine learning workflows, analytics and powers some of the products offered to Apollo customers. You'll develop and maintain scalable data pipelines and build new integrations to support continuing increases in data volume and complexity. You will also implement automated monitoring, alerting, self-healing features while building the consumption pipelines.

As a Data Engineer at Sporty, you will play a critical role in ensuring the smooth processing and handling of data for our machine learning and data science initiatives. Your primary responsibilities will include designing, building, testing, optimising, and maintaining data pipelines and architectures for various aspects of our rapidly growing business.