Galytix (GX) is delivering on the promise of AI.
GX has built specialised knowledge AI assistants for the banking and insurance industry. Our assistants are fed by sector-specific data and knowledge and easily adaptable through ontology layers to reflect institution-specific rules.
GX AI assistants are designed for Individual Investors, Credit and Claims professionals. Our assistants are being used right now in global financial institutions. Proven, trusted, non-hallucinating, our assistants are empowering financial professionals and delivering 10x improvements by supporting them in their day-to-day tasks.
Responsibilities: Helping to architect, design, implement, and optimise our data ingestion, transformation, and spreading pipelines and processes.
Developing data models, processing pipelines, and back-end services supporting the data science teams, automating processes, building integrations, and analytics.
Desired skills: A university degree in Mathematics, Computer Science, Engineering, Physics or similar.
5+ years of relevant experience in Data Engineering, warehousing, ETL, automation, cloud technologies, or Software Engineering in data related areas.
Ability to write clean, scalable, maintainable code in Python with a good understanding of software engineering concepts and patterns. Proficiency in other languages like Scala, Java, C#, C++ are an advantage.
Proven record of building and maintaining data pipelines deployed in at least one of the big 3 cloud ML stacks (AWS, Azure, GCP).
Hands-on experience with open-source ETL, and data pipeline orchestration tools such as Apache Airflow and Nifi.
Experience with large scale/Big Data technologies, such as Hadoop, Spark, Hive, Impala, PrestoDb, Kafka.
Experience with workflow orchestration tools like Apache Airflow.
Experience with containerisation using Docker and deployment on Kubernetes.
Experience with NoSQL and graph databases.
Unix server administration and shell scripting experience.
Experience in building scalable data pipelines for highly unstructured data.
Experience in building DWH and data lakes architectures.
Experience in working in cross-functional teams with software engineers, data scientists, and machine learning engineers.
Experience in working with or leading an off-shore team.
Proven record of building data science environments deploying ML solutions in at least one of the big 3 cloud ML stacks (Azure/AWS/GCP) and on Kubernetes clusters.
Excellent written and verbal command of English.
Strong problem-solving, analytical, and quantitative skills.
A professional attitude and service orientation with the ability to work with our international teams.
Why you do not want to miss this career opportunity? We are a mission-driven firm that is revolutionising the Insurance and Banking industry. We are not aiming to incrementally push the current boundaries; we redefine them.
Customer-centric organisation with innovation at the core of everything we do.
Capitalize on an unparalleled career progression opportunity.
Work closely with senior leaders who have individually served several CEOs in Fortune 100 companies globally.
Develop highly valued skills and build connections in the industry by working with top-tier Insurance and Banking clients on their mission-critical problems and deploying solutions integrated into their day-to-day workflows and processes.
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