As a Data Systems Engineer at Northbeam, you will translate customer feedback into scalable data pipelines and products, creating, maintaining, and improving integrations and transformations in a complex network. The system is powered by data that spans numerous ad platforms and order management systems, requiring curiosity, experience, and a desire to build data pipelines and applications at scale.
The Senior Software Engineer - Data will architect, implement, and optimize data models, pipelines, and storage solutions across Acquisition.com’s data ecosystem, ensuring reliability, performance, and accessibility of data. This individual will serve as a bridge between raw information and actionable business intelligence, taking complex data initiatives from concept to delivery.
As a Data Scientist on Plaid’s Fraud Data team, you will analyze customer and network traffic to understand how Protect performs across different segments and use cases. You’ll build dashboards and performance metrics that create a clear, shared view of product health for both the team and our go-to-market partners.
The Data Engineering team is focused on the design, development, and support for 'all things data' at OppFi. This includes the deployment of Postgres databases which support our applications, our Snowflake Data Warehouse and multiple Airflow and Hevo ETLs. You will work on Postgresql Database Administration and Data Engineering.
We’re hiring a Lead Product Scientist to help build our Product Analytics capabilities at Paddle. This role sits at the intersection of Product and Data — quantifying the impact of our product features through historical studies, setting up our experimentation culture, and enabling a cadence of reviewing feature performance.
As a Data Engineer on the Growth org, you will collaborate with our cross-functional partners in Data Science, Product, and Finance to build and maintain high quality data sources and build software that maximizes the value and efficacy of that data. The team operates independent of skill set, so your peers with software engineering backgrounds will execute on data engineering work, and you will make contributions on software systems that don’t directly work with our data systems.
This role involves collaborating with clients to understand their IT environments and digital transformation goals. Responsibilities include collecting and managing large volumes of data, creating robust data pipelines for Data Products, and defining data models that integrate disparate data. The role also includes performing data transformations using tools such as Spark, Trino, and AWS Athena and developing, testing, and deploying Data API Products with Python and frameworks like Flask or FastAPI.
Join a role for dynamic financial institution where your core aim is to unlock business insights from large datasets, empowering decision-makers across trading, investment, and research teams with robust analytics and data-driven projects. You will play a pivotal role in improving operational efficiency, developing scalable reporting frameworks, and enhancing performance tracking through advanced financial modeling and dashboard automation.
This crucial role involves managing and mentoring a team of professionals in Data Analytics and Business Intelligence. You will set the data strategy for the organization, driving business growth by transforming data into actionable insights. This role will oversee our analytics and BI ecosystem, built on both Google and Microsoft data solutions, with a clear roadmap to incorporate and lead the Data science and engineering skillsets in the future.
At Vattenfall, the mission is to help customers power their lives in climate smarter ways and enable a fossil free future. As a Data Engineer in the Data Science team, you will join a collaborative and skilled team that drives automation of real business cases through data-driven and Machine Learning-based intelligence. You will design, maintain, and monitor real-time and batch data pipelines, ingest and process external data feeds, and collaborate with Data Scientists and ML Engineers to build and maintain feature pipelines.