Remote Data Jobs · Spark

Transform terabytes of data into actionable insights as an Analytics Engineer on Kraken's Data Platform team, enabling us to stay ahead in the ever-evolving cryptocurrency landscape. You’ll work on Finance data, building data products for various Finance and analytics teams, and that’s where your Finance background and expertise, alongside with Analytics Engineering skills will help us succeed!

Design, build, and manage data warehouse to serve as the single source of truth for the organization. Develop and deploy low-latency, real-time data streaming pipelines. Enable self-service analytics by building clean, well-documented, and trusted datasets. Establish and follow data governance and security best practices. Stay current with industry best practices and emerging data analysis tools and techniques.

We are seeking a skilled and motivated Artificial Intelligence Engineer to join our team. This role offers the opportunity to design, build, and deploy advanced artificial intelligence solutions across a variety of projects. You will work with large datasets, machine learning models, and cloud technologies to deliver innovative, high-impact results.

The Data Platform Engineering team is building the foundation for a best-in-class decision engine—empowering data scientists, machine learning engineers, and analytics teams to deliver insights and intelligence at scale. As a Data Platform Engineer, you’ll design, build, and evolve the infrastructure and tooling that enable our internal teams to move fast, work efficiently, and make data-driven decisions.

Develop new novel and state of the art AI/machine learning models to support risk strategies. Recommend data-driven, risk-based business decisions to positively impact KPIs across Trustly's payment portfolio. Conduct analysis to measure model performance, compare performance across multiple models, and influence model strategy and selection decisions.

Design and build a next-gen data platform for one of Blue Coding's clients, leading the end-to-end ingestion, transformation, and governance of document-centric datasets stored in S3. Set up a scalable data lake and warehouse that powers analytics, dashboards, and AI model training. Balance hands-on engineering with clear stakeholder communication, turning client feedback into actionable sprint plans.

As a Data Scientist, you will help develop analytical solutions, contributing to product prototypes, and helping evaluate data assets. You will bring experience in predictive modeling, machine learning, and deep learning to this position. Craft advanced machine learning analytical solutions to extract insights from diverse structured and unstructured data sources.

Use your software engineering skills, including Java, Spark, Python, Scala, to Analyze different, complex systems and collaboratively design new products and services Integrate new data sources and tools Implement scalable and reliable distributed data replication strategies Mentor and provide direction in architecture and design to onsite/offshore developers. As a Big Data Engineer, you will report to the Director, Software Development.

Looking for a highly skilled Databricks Data Architect to lead the design, development, and implementation of a modern hub-and-spoke data platform for a leading retail company. This platform will serve as the foundation for advanced analytics and real-time personalization, enabling data-driven decision-making and customer engagement. The role involves working closely with business stakeholders, data engineers, and product teams to design scalable, secure, and efficient data solutions on Databricks and the modern data stack.

Design and deliver machine learning solutions that combine modern research with practical deployment. Contribute to building robust models that power client-facing tools and internal platforms. Integrate models into deployable systems operating in production environments. Engage with stakeholders to frame ambiguous problems, explore solution paths, and translate technical insights into practical outcomes.